datasetId stringlengths 2 117 | card stringlengths 19 1.01M |
|---|---|
CyberHarem/hatsuchiri_neuralcloud | ---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---
# Dataset of hatsuchiri/初塵/初尘 (Neural Cloud)
This is the dataset of hatsuchiri/初塵/初尘 (Neural Cloud), containing 29 images and their tags.
The core tags of this character are `bangs, breasts, black_hair, mole, hair_ornament, hair_between_eyes, hairclip, mole_under_eye, red_eyes, long_hair, small_breasts, brown_hair`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 29 | 65.26 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hatsuchiri_neuralcloud/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 29 | 29.03 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hatsuchiri_neuralcloud/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 77 | 66.88 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hatsuchiri_neuralcloud/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 29 | 54.28 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hatsuchiri_neuralcloud/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 77 | 110.77 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hatsuchiri_neuralcloud/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/hatsuchiri_neuralcloud',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 5 |  |  |  |  |  | 1girl, bikini_top_only, black_bikini, bare_shoulders, black_gloves, black_jacket, front-tie_bikini_top, looking_at_viewer, necklace, off_shoulder, solo, closed_mouth, open_jacket, tentacles, blurry, bubble, choker, helmet, long_sleeves, mole_on_breast, motorcycle, navel, parted_lips, simple_background, sitting, stomach, white_background |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | bikini_top_only | black_bikini | bare_shoulders | black_gloves | black_jacket | front-tie_bikini_top | looking_at_viewer | necklace | off_shoulder | solo | closed_mouth | open_jacket | tentacles | blurry | bubble | choker | helmet | long_sleeves | mole_on_breast | motorcycle | navel | parted_lips | simple_background | sitting | stomach | white_background |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:------------------|:---------------|:-----------------|:---------------|:---------------|:-----------------------|:--------------------|:-----------|:---------------|:-------|:---------------|:--------------|:------------|:---------|:---------|:---------|:---------|:---------------|:-----------------|:-------------|:--------|:--------------|:--------------------|:----------|:----------|:-------------------|
| 0 | 5 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |
|
CyberHarem/exia_nikke | ---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---
# Dataset of exia/エクシア/艾可希雅/엑시아 (Nikke: Goddess of Victory)
This is the dataset of exia/エクシア/艾可希雅/엑시아 (Nikke: Goddess of Victory), containing 70 images and their tags.
The core tags of this character are `long_hair, hair_between_eyes, headphones, black_hair, purple_eyes, bangs, breasts`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 70 | 124.30 MiB | [Download](https://huggingface.co/datasets/CyberHarem/exia_nikke/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 70 | 55.86 MiB | [Download](https://huggingface.co/datasets/CyberHarem/exia_nikke/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 181 | 127.97 MiB | [Download](https://huggingface.co/datasets/CyberHarem/exia_nikke/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 70 | 101.73 MiB | [Download](https://huggingface.co/datasets/CyberHarem/exia_nikke/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 181 | 204.43 MiB | [Download](https://huggingface.co/datasets/CyberHarem/exia_nikke/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/exia_nikke',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 6 |  |  |  |  |  | 1girl, shirt, solo, black_panties, looking_at_viewer, off_shoulder, simple_background, ass, can, monster_energy, thighs, white_background |
| 1 | 16 |  |  |  |  |  | 1girl, solo, off_shoulder, nail_polish, bare_shoulders, black_choker, collarbone, jacket, looking_at_viewer, closed_mouth, long_sleeves, white_shirt, black_nails, holding_handheld_game_console, nintendo_switch |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | shirt | solo | black_panties | looking_at_viewer | off_shoulder | simple_background | ass | can | monster_energy | thighs | white_background | nail_polish | bare_shoulders | black_choker | collarbone | jacket | closed_mouth | long_sleeves | white_shirt | black_nails | holding_handheld_game_console | nintendo_switch |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------|:-------|:----------------|:--------------------|:---------------|:--------------------|:------|:------|:-----------------|:---------|:-------------------|:--------------|:-----------------|:---------------|:-------------|:---------|:---------------|:---------------|:--------------|:--------------|:--------------------------------|:------------------|
| 0 | 6 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | |
| 1 | 16 |  |  |  |  |  | X | | X | | X | X | | | | | | | X | X | X | X | X | X | X | X | X | X | X |
|
Sampath1987/NER_cyber_1 | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 1676604
num_examples: 2481
download_size: 358027
dataset_size: 1676604
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
Norod78/drwho-weeping-angels-blip2-captions-512 | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 31177714.0
num_examples: 95
download_size: 31179138
dataset_size: 31177714.0
---
# Dataset Card for "drwho-weeping-angels-blip2-captions-512"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
allenai/mup | ---
license:
- odc-by
---
# MuP - Multi Perspective Scientific Document Summarization
Generating summaries of scientific documents is known to be a challenging task. Majority of existing work in summarization assumes only one single best gold summary for each given document. Having only one gold summary negatively impacts our ability to evaluate the quality of summarization systems as writing summaries is a subjective activity. At the same time, annotating multiple gold summaries for scientific documents can be extremely expensive as it requires domain experts to read and understand long scientific documents. This shared task will enable exploring methods for generating multi-perspective summaries. We introduce a novel summarization corpus, leveraging data from scientific peer reviews to capture diverse perspectives from the reader's point of view.
|
chenbobo/chat_train | ---
license: unlicense
---
|
results-sd-v1-5-sd-v2-1-if-v1-0-karlo/ce0524fd | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 186
num_examples: 10
download_size: 1331
dataset_size: 186
---
# Dataset Card for "ce0524fd"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
sczssczxz/venti | ---
license: openrail
---
|
Nicolas-BZRD/DEBATS_opendata | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: train
num_bytes: 860286530
num_examples: 2214
download_size: 438989465
dataset_size: 860286530
license: odc-by
language:
- fr
tags:
- legal
pretty_name: Debates at National Assembly and Senate
size_categories:
- 1K<n<10K
---
# DEBATS (National Assembly and Senate)
The database contains full reports of french [debates](https://echanges.dila.gouv.fr/OPENDATA/Debats/) in the National Assembly since October 4, 2011 and in the Senate since October 2, 2011. |
Lollitor/ForwardScreening | ---
dataset_info:
features:
- name: '#code'
dtype: string
- name: inputs
dtype: string
splits:
- name: train
num_bytes: 16350621
num_examples: 16245
download_size: 1806661
dataset_size: 16350621
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "ForwardScreening"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
shunk031/jsnli | ---
language:
- ja
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
task_categories:
- text-classification
task_ids:
- natural-language-inference
- multi-input-text-classification
tags:
- natural-language-inference
- nli
- jsnli
datasets:
- without-filtering
- with-filtering
metrics:
- accuracy
---
# Dataset Card for JSNLI
[](https://github.com/shunk031/huggingface-datasets_jsnli/actions/workflows/ci.yaml)
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Dataset Preprocessing](#dataset-preprocessing)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- Homepage: https://nlp.ist.i.kyoto-u.ac.jp/?%E6%97%A5%E6%9C%AC%E8%AA%9ESNLI%28JSNLI%29%E3%83%87%E3%83%BC%E3%82%BF%E3%82%BB%E3%83%83%E3%83%88
- Repository: https://github.com/shunk031/huggingface-datasets_jsnli
### Dataset Summary
[日本語 SNLI(JSNLI) データセット - KUROHASHI-CHU-MURAWAKI LAB](https://nlp.ist.i.kyoto-u.ac.jp/?%E6%97%A5%E6%9C%AC%E8%AA%9ESNLI%28JSNLI%29%E3%83%87%E3%83%BC%E3%82%BF%E3%82%BB%E3%83%83%E3%83%88 ) より：
> 本データセットは自然言語推論 (NLI) の標準的ベンチマークである [SNLI](https://nlp.stanford.edu/projects/snli/) を日本語に翻訳したものです。
### Dataset Preprocessing
### Supported Tasks and Leaderboards
### Languages
注釈はすべて日本語を主要言語としています。
## Dataset Structure
> データセットは TSV フォーマットで、各行がラベル、前提、仮説の三つ組を表します。前提、仮説は JUMAN++ によって形態素分割されています。以下に例をあげます。
```
entailment 自転車 で ２ 人 の 男性 が レース で 競い ます 。 人々 は 自転車 に 乗って います 。
```
### Data Instances
```python
from datasets import load_dataset
load_dataset("shunk031/jsnli", "without-filtering")
```
```json
{
'label': 'neutral',
'premise': 'ガレージ で 、 壁 に ナイフ を 投げる 男 。',
'hypothesis': '男 は 魔法 の ショー の ため に ナイフ を 投げる 行為 を 練習 して い ます 。'
}
```
### Data Fields
### Data Splits
| name | train | validation |
|-------------------|--------:|-----------:|
| without-filtering | 548,014 | 3,916 |
| with-filtering | 533,005 | 3,916 |
## Dataset Creation
### Curation Rationale
### Source Data
#### Initial Data Collection and Normalization
#### Who are the source language producers?
### Annotations
#### Annotation process
> SNLI に機械翻訳を適用した後、評価データにクラウドソーシングによる正確なフィルタリング、学習データに計算機による自動フィルタリングを施すことで構築されています。
> データセットは学習データを全くフィルタリングしていないものと、フィルタリングした中で最も精度が高かったものの 2 種類を公開しています。データサイズは、フィルタリング前の学習データが 548,014 ペア、フィルタリング後の学習データが 533,005 ペア、評価データは 3,916 ペアです。詳細は参考文献を参照してください。
#### Who are the annotators?
### Personal and Sensitive Information
## Considerations for Using the Data
### Social Impact of Dataset
### Discussion of Biases
### Other Known Limitations
## Additional Information
> 本データセットに関するご質問は nl-resource あっと nlp.ist.i.kyoto-u.ac.jp 宛にお願いいたします。
### Dataset Curators
### Licensing Information
> このデータセットのライセンスは、SNLI のライセンスと同じ [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/) に従います。SNLI に関しては参考文献を参照してください。
### Citation Information
```bibtex
@article{吉越卓見 2020 機械翻訳を用いた自然言語推論データセットの多言語化，
title={機械翻訳を用いた自然言語推論データセットの多言語化},
author={吉越卓見 and 河原大輔 and 黒橋禎夫 and others},
journal={研究報告自然言語処理 (NL)},
volume={2020},
number={6},
pages={1--8},
year={2020}
}
```
```bibtex
@inproceedings{bowman2015large,
title={A large annotated corpus for learning natural language inference},
author={Bowman, Samuel and Angeli, Gabor and Potts, Christopher and Manning, Christopher D},
booktitle={Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing},
pages={632--642},
year={2015}
}
```
```bibtex
@article{young2014image,
title={From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions},
author={Young, Peter and Lai, Alice and Hodosh, Micah and Hockenmaier, Julia},
journal={Transactions of the Association for Computational Linguistics},
volume={2},
pages={67--78},
year={2014},
publisher={MIT Press}
}
```
### Contributions
JSNLI データセットを公開してくださった吉越 卓見さま，河原 大輔さま，黒橋 禎夫さまに心から感謝します。
|
thakurvishesh1/good_prompt | ---
license: openrail
---
|
molchomen/colors_matching | ---
license: mit
task_categories:
- text2text-generation
language:
- aa
tags:
- finance
size_categories:
- n<1K
--- |
results-sd-v1-5-sd-v2-1-if-v1-0-karlo/3a222eb5 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 180
num_examples: 10
download_size: 1336
dataset_size: 180
---
# Dataset Card for "3a222eb5"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Rasi1610/DeathSe46_series2_p2 | ---
dataset_info:
features:
- name: image
dtype: image
- name: ground_truth
dtype: string
splits:
- name: train
num_bytes: 223332981.0
num_examples: 229
- name: val
num_bytes: 55959743.0
num_examples: 58
download_size: 278833929
dataset_size: 279292724.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: val
path: data/val-*
---
|
distilled-from-one-sec-cv12/chunk_75 | ---
dataset_info:
features:
- name: logits
sequence: float32
- name: mfcc
sequence:
sequence: float64
splits:
- name: train
num_bytes: 1245038596
num_examples: 242603
download_size: 1270666206
dataset_size: 1245038596
---
# Dataset Card for "chunk_75"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Tesselexo/Mars-citizen-city-blue-mainframe-siriusABtransmission-data | ---
license: mit
---
|
mask-distilled-one-sec-cv12/chunk_210 | ---
dataset_info:
features:
- name: logits
sequence: float32
- name: mfcc
sequence:
sequence: float64
splits:
- name: train
num_bytes: 1123132256
num_examples: 220568
download_size: 1147587111
dataset_size: 1123132256
---
# Dataset Card for "chunk_210"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Roboos/Harry-bot | ---
license: unknown
---
|
tazarov/dst12345 | ---
language: en
license: mit
size_categories:
- n<1K
pretty_name: Chroma export of collection 4421321
dataset_info:
features:
- name: id
dtype: string
- name: embedding
sequence: float32
- name: document
dtype: string
- name: metadata._id
dtype: string
- name: metadata.title
dtype: string
splits:
- name: train
num_bytes: 1320534
num_examples: 200
download_size: 1297705
dataset_size: 1320534
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
x-chroma:
description: Chroma Dataset for collection 4421321
collection: '4421321'
metadata:
hnsw:space: ip
test: 123
---
# Dataset Card for "dst12345"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)+ |
rinabuoy/Khmer-ALT-Flores-GTran-SSBIC-2Ways-Mistral-V2 | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 62934976
num_examples: 150584
- name: test
num_bytes: 5521786
num_examples: 11822
download_size: 16178214
dataset_size: 68456762
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
|
shibing624/sts-sohu2021 | ---
annotations_creators:
- shibing624
language_creators:
- shibing624
language:
- zh
license:
- cc-by-4.0
multilinguality:
- zh
size_categories:
- 100K<n<20M
source_datasets:
- https://www.biendata.xyz/competition/sohu_2021/data/
task_categories:
- text-classification
- sentence-similarity
task_ids:
- natural-language-inference
- semantic-similarity-scoring
- text-scoring
paperswithcode_id: sts
pretty_name: Sentence Text Similarity SOHU2021
---
# Dataset Card for sts-sohu2021
## Dataset Description
- **Repository:** [Chinese NLI dataset](https://github.com/shibing624/text2vec)
- **Leaderboard:** [NLI_zh leaderboard](https://github.com/shibing624/text2vec) (located on the homepage)
- **Size of downloaded dataset files:** 218 MB
- **Total amount of disk used:** 218 MB
### Dataset Summary
2021搜狐校园文本匹配算法大赛数据集
- 数据源：https://www.biendata.xyz/competition/sohu_2021/data/
分为 A 和 B 两个文件，A 和 B 文件匹配标准不一样。其中 A 和 B 文件又分为“短短文本匹配”、“短长文本匹配”和“长长文本匹配”。
A 文件匹配标准较为宽泛，两段文字是同一个话题便视为匹配，B 文件匹配标准较为严格，两段文字须是同一个事件才视为匹配。
数据类型：
| type | 数据类型 |
| --- | ------------|
| dda | 短短匹配 A 类 |
| ddb | 短短匹配 B 类 |
| dca | 短长匹配 A 类 |
| dcb | 短长匹配 B 类 |
| cca | 长长匹配 A 类 |
| ccb | 长长匹配 B 类 |
### Supported Tasks and Leaderboards
Supported Tasks: 支持中文文本匹配任务，文本相似度计算等相关任务。
中文匹配任务的结果目前在顶会paper上出现较少，我罗列一个我自己训练的结果：
**Leaderboard:** [NLI_zh leaderboard](https://github.com/shibing624/text2vec)
### Languages
数据集均是简体中文文本。
## Dataset Structure
### Data Instances
An example of 'train' looks as follows.
```python
# A 类 短短 样本示例
{
"sentence1": "小艺的故事让爱回家2021年2月16日大年初五19：30带上你最亲爱的人与团团君相约《小艺的故事》直播间！",
"sentence2": "香港代购了不起啊，宋点卷竟然在直播间“炫富”起来",
"label": 0
}
# B 类 短短 样本示例
{
"sentence1": "让很多网友好奇的是，张柏芝在一小时后也在社交平台发文：“给大家拜年啦。”还有网友猜测：谢霆锋的经纪人发文，张柏芝也发文，并且配图，似乎都在证实，谢霆锋依旧和王菲在一起，而张柏芝也有了新的恋人，并且生了孩子，两人也找到了各自的归宿，有了自己的幸福生活，让传言不攻自破。",
"sentence2": "陈晓东谈旧爱张柏芝，一个口误暴露她的秘密，难怪谢霆锋会离开她",
"label": 0
}
```
label: 0表示不匹配，1表示匹配。
### Data Fields
The data fields are the same among all splits.
- `sentence1`: a `string` feature.
- `sentence2`: a `string` feature.
- `label`: a classification label, with possible values including `similarity` (1), `dissimilarity` (0).
### Data Splits
```shell
> wc -l *.jsonl
11690 cca.jsonl
11690 ccb.jsonl
11592 dca.jsonl
11593 dcb.jsonl
11512 dda.jsonl
11501 ddb.jsonl
69578 total
```
### Curation Rationale
作为中文NLI(natural langauge inference)数据集，这里把这个数据集上传到huggingface的datasets，方便大家使用。
#### Who are the source language producers?
数据集的版权归原作者所有，使用各数据集时请尊重原数据集的版权。
#### Who are the annotators?
原作者。
### Social Impact of Dataset
This dataset was developed as a benchmark for evaluating representational systems for text, especially including those induced by representation learning methods, in the task of predicting truth conditions in a given context.
Systems that are successful at such a task may be more successful in modeling semantic representations.
### Licensing Information
用于学术研究。
### Contributions
[shibing624](https://github.com/shibing624) upload this dataset. |
kpriyanshu256/MultiTabQA-multitable_pretraining-Salesforce-codet5-base_train-html-63000 | ---
dataset_info:
features:
- name: input_ids
sequence:
sequence: int32
- name: attention_mask
sequence:
sequence: int8
- name: labels
sequence:
sequence: int64
splits:
- name: train
num_bytes: 13336000
num_examples: 1000
download_size: 653228
dataset_size: 13336000
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
arsalanaa/Hoilpainting_regularization_768X768_3000 | ---
license: unknown
---
|
luxinyi/tagged_articles | ---
dataset_info:
features:
- name: Published
dtype: string
- name: Index
dtype: string
- name: Sub Index
dtype: 'null'
- name: Headline
dtype: string
- name: Summary
dtype: string
- name: Facebook Interactions
dtype: int64
- name: Download Date
dtype: string
- name: Theme
dtype: string
- name: New Index
dtype: string
- name: New Sub Index
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 420130.5018248175
num_examples: 1315
- name: validation
num_bytes: 105112.49817518248
num_examples: 329
download_size: 305631
dataset_size: 525243.0
---
# Dataset Card for "tagged_articles"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
gokulraja17/rice-rgb-demo2 | ---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': RiceLeafs_BrownSpot
'1': RiceLeafs_Healthy
'2': RiceLeafs_Hispa
'3': RiceLeafs_LeafBlast
splits:
- name: train
num_bytes: 11929981.02
num_examples: 2683
- name: test
num_bytes: 3059814.0
num_examples: 672
download_size: 14605882
dataset_size: 14989795.02
---
# Dataset Card for "rice-rgb-demo2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Amod/mental_health_counseling_conversations | ---
license: openrail
task_categories:
- text-generation
- question-answering
language:
- en
tags:
- medical
size_categories:
- 1K<n<10K
---
# Amod/mental_health_counseling_conversations
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-instances)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:** Bertagnolli, Nicolas (2020). Counsel chat: Bootstrapping high-quality therapy data. Towards Data Science. https://towardsdatascience.com/counsel-chat
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
This dataset is a collection of questions and answers sourced from two online counseling and therapy platforms. The questions cover a wide range of mental health topics, and the answers are provided by qualified psychologists. The dataset is intended to be used for fine-tuning language models to improve their ability to provide mental health advice.
### Supported Tasks and Leaderboards
The dataset supports the task of text generation, particularly for generating advice or suggestions in response to a mental health-related question.
### Languages
The text in the dataset is in English.
## Dataset Structure
### Data Instances
A data instance includes a 'Context' and a 'Response'. 'Context' contains the question asked by a user, and 'Response' contains the corresponding answer provided by a psychologist.
### Data Fields
- 'Context': a string containing the question asked by a user
- 'Response': a string containing the corresponding answer provided by a psychologist
### Data Splits
The dataset has no predefined splits. Users can create their own splits as needed.
## Dataset Creation
### Curation Rationale
This dataset was created to aid in the development of AI models that can provide mental health advice or guidance. The raw data was meticulously cleaned to only include the conversations.
### Source Data
The data was sourced from two online counseling and therapy platforms. The raw data can be found [here](https://github.com/nbertagnolli/counsel-chat/tree/master/data).
### Annotations
The dataset does not contain any additional annotations.
### Personal and Sensitive Information
The dataset may contain sensitive information related to mental health. All data was anonymized and no personally identifiable information is included. |
rghosh8/supportGPT-v8 | ---
license: bsd
---
|
Bluebomber182/Poppy-From-Trolls | ---
license: unknown
---
|
open-llm-leaderboard/details_maximuslee07__llama-2-13b-rockwellautomation | ---
pretty_name: Evaluation run of maximuslee07/llama-2-13b-rockwellautomation
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [maximuslee07/llama-2-13b-rockwellautomation](https://huggingface.co/maximuslee07/llama-2-13b-rockwellautomation)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 63 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the aggregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_maximuslee07__llama-2-13b-rockwellautomation\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2024-01-04T15:04:41.345460](https://huggingface.co/datasets/open-llm-leaderboard/details_maximuslee07__llama-2-13b-rockwellautomation/blob/main/results_2024-01-04T15-04-41.345460.json)(note\
\ that their might be results for other tasks in the repos if successive evals didn't\
\ cover the same tasks. You find each in the results and the \"latest\" split for\
\ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.2511081603813156,\n\
\ \"acc_stderr\": 0.030845430828452477,\n \"acc_norm\": 0.2520379726970298,\n\
\ \"acc_norm_stderr\": 0.031666273642418356,\n \"mc1\": 0.24357405140758873,\n\
\ \"mc1_stderr\": 0.015026354824910782,\n \"mc2\": NaN,\n \"\
mc2_stderr\": NaN\n },\n \"harness|arc:challenge|25\": {\n \"acc\"\
: 0.23378839590443687,\n \"acc_stderr\": 0.012368225378507148,\n \"\
acc_norm\": 0.2815699658703072,\n \"acc_norm_stderr\": 0.013143376735009015\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.2548297151961761,\n\
\ \"acc_stderr\": 0.004348748730529937,\n \"acc_norm\": 0.2577175861382195,\n\
\ \"acc_norm_stderr\": 0.00436483800033562\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.26,\n \"acc_stderr\": 0.04408440022768077,\n \
\ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.04408440022768077\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.28888888888888886,\n\
\ \"acc_stderr\": 0.0391545063041425,\n \"acc_norm\": 0.28888888888888886,\n\
\ \"acc_norm_stderr\": 0.0391545063041425\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.25,\n \"acc_stderr\": 0.03523807393012047,\n \
\ \"acc_norm\": 0.25,\n \"acc_norm_stderr\": 0.03523807393012047\n \
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.18,\n\
\ \"acc_stderr\": 0.03861229196653695,\n \"acc_norm\": 0.18,\n \
\ \"acc_norm_stderr\": 0.03861229196653695\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.2830188679245283,\n \"acc_stderr\": 0.027724236492700907,\n\
\ \"acc_norm\": 0.2830188679245283,\n \"acc_norm_stderr\": 0.027724236492700907\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.2638888888888889,\n\
\ \"acc_stderr\": 0.03685651095897532,\n \"acc_norm\": 0.2638888888888889,\n\
\ \"acc_norm_stderr\": 0.03685651095897532\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \
\ \"acc_norm\": 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\
: 0.33,\n \"acc_stderr\": 0.047258156262526045,\n \"acc_norm\": 0.33,\n\
\ \"acc_norm_stderr\": 0.047258156262526045\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \
\ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.24855491329479767,\n\
\ \"acc_stderr\": 0.03295304696818318,\n \"acc_norm\": 0.24855491329479767,\n\
\ \"acc_norm_stderr\": 0.03295304696818318\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.27450980392156865,\n \"acc_stderr\": 0.044405219061793275,\n\
\ \"acc_norm\": 0.27450980392156865,\n \"acc_norm_stderr\": 0.044405219061793275\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \"acc_norm\": 0.25,\n\
\ \"acc_norm_stderr\": 0.04351941398892446\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.2,\n \"acc_stderr\": 0.026148818018424502,\n \
\ \"acc_norm\": 0.2,\n \"acc_norm_stderr\": 0.026148818018424502\n \
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.2631578947368421,\n\
\ \"acc_stderr\": 0.041424397194893624,\n \"acc_norm\": 0.2631578947368421,\n\
\ \"acc_norm_stderr\": 0.041424397194893624\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.3103448275862069,\n \"acc_stderr\": 0.03855289616378948,\n\
\ \"acc_norm\": 0.3103448275862069,\n \"acc_norm_stderr\": 0.03855289616378948\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.2619047619047619,\n \"acc_stderr\": 0.022644212615525218,\n \"\
acc_norm\": 0.2619047619047619,\n \"acc_norm_stderr\": 0.022644212615525218\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.29365079365079366,\n\
\ \"acc_stderr\": 0.040735243221471255,\n \"acc_norm\": 0.29365079365079366,\n\
\ \"acc_norm_stderr\": 0.040735243221471255\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.28,\n \"acc_stderr\": 0.04512608598542128,\n \
\ \"acc_norm\": 0.28,\n \"acc_norm_stderr\": 0.04512608598542128\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.25161290322580643,\n\
\ \"acc_stderr\": 0.024685979286239963,\n \"acc_norm\": 0.25161290322580643,\n\
\ \"acc_norm_stderr\": 0.024685979286239963\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\
: {\n \"acc\": 0.2019704433497537,\n \"acc_stderr\": 0.02824735012218026,\n\
\ \"acc_norm\": 0.2019704433497537,\n \"acc_norm_stderr\": 0.02824735012218026\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.23,\n \"acc_stderr\": 0.04229525846816506,\n \"acc_norm\"\
: 0.23,\n \"acc_norm_stderr\": 0.04229525846816506\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.2787878787878788,\n \"acc_stderr\": 0.03501438706296781,\n\
\ \"acc_norm\": 0.2787878787878788,\n \"acc_norm_stderr\": 0.03501438706296781\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.2878787878787879,\n \"acc_stderr\": 0.03225883512300992,\n \"\
acc_norm\": 0.2878787878787879,\n \"acc_norm_stderr\": 0.03225883512300992\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.23316062176165803,\n \"acc_stderr\": 0.030516111371476008,\n\
\ \"acc_norm\": 0.23316062176165803,\n \"acc_norm_stderr\": 0.030516111371476008\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.21794871794871795,\n \"acc_stderr\": 0.02093244577446317,\n\
\ \"acc_norm\": 0.21794871794871795,\n \"acc_norm_stderr\": 0.02093244577446317\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.28888888888888886,\n \"acc_stderr\": 0.027634907264178544,\n \
\ \"acc_norm\": 0.28888888888888886,\n \"acc_norm_stderr\": 0.027634907264178544\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.25630252100840334,\n \"acc_stderr\": 0.02835962087053395,\n\
\ \"acc_norm\": 0.25630252100840334,\n \"acc_norm_stderr\": 0.02835962087053395\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.2582781456953642,\n \"acc_stderr\": 0.035737053147634576,\n \"\
acc_norm\": 0.2582781456953642,\n \"acc_norm_stderr\": 0.035737053147634576\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.25137614678899084,\n \"acc_stderr\": 0.018599206360287415,\n \"\
acc_norm\": 0.25137614678899084,\n \"acc_norm_stderr\": 0.018599206360287415\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.2037037037037037,\n \"acc_stderr\": 0.027467401804058014,\n \"\
acc_norm\": 0.2037037037037037,\n \"acc_norm_stderr\": 0.027467401804058014\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.20098039215686275,\n \"acc_stderr\": 0.028125972265654355,\n \"\
acc_norm\": 0.20098039215686275,\n \"acc_norm_stderr\": 0.028125972265654355\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.24472573839662448,\n \"acc_stderr\": 0.027985699387036416,\n \
\ \"acc_norm\": 0.24472573839662448,\n \"acc_norm_stderr\": 0.027985699387036416\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.1210762331838565,\n\
\ \"acc_stderr\": 0.02189417411318574,\n \"acc_norm\": 0.1210762331838565,\n\
\ \"acc_norm_stderr\": 0.02189417411318574\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.25190839694656486,\n \"acc_stderr\": 0.03807387116306085,\n\
\ \"acc_norm\": 0.25190839694656486,\n \"acc_norm_stderr\": 0.03807387116306085\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.2809917355371901,\n \"acc_stderr\": 0.041032038305145124,\n \"\
acc_norm\": 0.2809917355371901,\n \"acc_norm_stderr\": 0.041032038305145124\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.25925925925925924,\n\
\ \"acc_stderr\": 0.04236511258094632,\n \"acc_norm\": 0.25925925925925924,\n\
\ \"acc_norm_stderr\": 0.04236511258094632\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.2392638036809816,\n \"acc_stderr\": 0.03351953879521269,\n\
\ \"acc_norm\": 0.2392638036809816,\n \"acc_norm_stderr\": 0.03351953879521269\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.26785714285714285,\n\
\ \"acc_stderr\": 0.04203277291467764,\n \"acc_norm\": 0.26785714285714285,\n\
\ \"acc_norm_stderr\": 0.04203277291467764\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.20388349514563106,\n \"acc_stderr\": 0.039891398595317706,\n\
\ \"acc_norm\": 0.20388349514563106,\n \"acc_norm_stderr\": 0.039891398595317706\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.25213675213675213,\n\
\ \"acc_stderr\": 0.02844796547623101,\n \"acc_norm\": 0.25213675213675213,\n\
\ \"acc_norm_stderr\": 0.02844796547623101\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.27,\n \"acc_stderr\": 0.044619604333847394,\n \
\ \"acc_norm\": 0.27,\n \"acc_norm_stderr\": 0.044619604333847394\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.22349936143039592,\n\
\ \"acc_stderr\": 0.014897235229450708,\n \"acc_norm\": 0.22349936143039592,\n\
\ \"acc_norm_stderr\": 0.014897235229450708\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.25722543352601157,\n \"acc_stderr\": 0.023532925431044276,\n\
\ \"acc_norm\": 0.25722543352601157,\n \"acc_norm_stderr\": 0.023532925431044276\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.21787709497206703,\n\
\ \"acc_stderr\": 0.013806211780732972,\n \"acc_norm\": 0.21787709497206703,\n\
\ \"acc_norm_stderr\": 0.013806211780732972\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.24836601307189543,\n \"acc_stderr\": 0.024739981355113592,\n\
\ \"acc_norm\": 0.24836601307189543,\n \"acc_norm_stderr\": 0.024739981355113592\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.26366559485530544,\n\
\ \"acc_stderr\": 0.02502553850053234,\n \"acc_norm\": 0.26366559485530544,\n\
\ \"acc_norm_stderr\": 0.02502553850053234\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.25925925925925924,\n \"acc_stderr\": 0.02438366553103546,\n\
\ \"acc_norm\": 0.25925925925925924,\n \"acc_norm_stderr\": 0.02438366553103546\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.26595744680851063,\n \"acc_stderr\": 0.026358065698880585,\n \
\ \"acc_norm\": 0.26595744680851063,\n \"acc_norm_stderr\": 0.026358065698880585\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.2392438070404172,\n\
\ \"acc_stderr\": 0.010896123652676644,\n \"acc_norm\": 0.2392438070404172,\n\
\ \"acc_norm_stderr\": 0.010896123652676644\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.23897058823529413,\n \"acc_stderr\": 0.025905280644893006,\n\
\ \"acc_norm\": 0.23897058823529413,\n \"acc_norm_stderr\": 0.025905280644893006\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.27941176470588236,\n \"acc_stderr\": 0.018152871051538816,\n \
\ \"acc_norm\": 0.27941176470588236,\n \"acc_norm_stderr\": 0.018152871051538816\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.22727272727272727,\n\
\ \"acc_stderr\": 0.040139645540727756,\n \"acc_norm\": 0.22727272727272727,\n\
\ \"acc_norm_stderr\": 0.040139645540727756\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.23673469387755103,\n \"acc_stderr\": 0.02721283588407315,\n\
\ \"acc_norm\": 0.23673469387755103,\n \"acc_norm_stderr\": 0.02721283588407315\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.2935323383084577,\n\
\ \"acc_stderr\": 0.03220024104534205,\n \"acc_norm\": 0.2935323383084577,\n\
\ \"acc_norm_stderr\": 0.03220024104534205\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \
\ \"acc_norm\": 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n \
\ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.21686746987951808,\n\
\ \"acc_stderr\": 0.03208284450356365,\n \"acc_norm\": 0.21686746987951808,\n\
\ \"acc_norm_stderr\": 0.03208284450356365\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.2631578947368421,\n \"acc_stderr\": 0.033773102522091945,\n\
\ \"acc_norm\": 0.2631578947368421,\n \"acc_norm_stderr\": 0.033773102522091945\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.24357405140758873,\n\
\ \"mc1_stderr\": 0.015026354824910782,\n \"mc2\": NaN,\n \"\
mc2_stderr\": NaN\n },\n \"harness|winogrande|5\": {\n \"acc\": 0.4980268350434096,\n\
\ \"acc_stderr\": 0.014052376259225632\n },\n \"harness|gsm8k|5\":\
\ {\n \"acc\": 0.0,\n \"acc_stderr\": 0.0\n }\n}\n```"
repo_url: https://huggingface.co/maximuslee07/llama-2-13b-rockwellautomation
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|arc:challenge|25_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|gsm8k|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hellaswag|10_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-01-04T15-04-41.345460.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-management|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-virology|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|truthfulqa:mc|0_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2024-01-04T15-04-41.345460.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- '**/details_harness|winogrande|5_2024-01-04T15-04-41.345460.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2024-01-04T15-04-41.345460.parquet'
- config_name: results
data_files:
- split: 2024_01_04T15_04_41.345460
path:
- results_2024-01-04T15-04-41.345460.parquet
- split: latest
path:
- results_2024-01-04T15-04-41.345460.parquet
---
# Dataset Card for Evaluation run of maximuslee07/llama-2-13b-rockwellautomation
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [maximuslee07/llama-2-13b-rockwellautomation](https://huggingface.co/maximuslee07/llama-2-13b-rockwellautomation) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_maximuslee07__llama-2-13b-rockwellautomation",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-01-04T15:04:41.345460](https://huggingface.co/datasets/open-llm-leaderboard/details_maximuslee07__llama-2-13b-rockwellautomation/blob/main/results_2024-01-04T15-04-41.345460.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"acc": 0.2511081603813156,
"acc_stderr": 0.030845430828452477,
"acc_norm": 0.2520379726970298,
"acc_norm_stderr": 0.031666273642418356,
"mc1": 0.24357405140758873,
"mc1_stderr": 0.015026354824910782,
"mc2": NaN,
"mc2_stderr": NaN
},
"harness|arc:challenge|25": {
"acc": 0.23378839590443687,
"acc_stderr": 0.012368225378507148,
"acc_norm": 0.2815699658703072,
"acc_norm_stderr": 0.013143376735009015
},
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"harness|hendrycksTest-high_school_world_history|5": {
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"harness|hendrycksTest-security_studies|5": {
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"harness|hendrycksTest-sociology|5": {
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"harness|hendrycksTest-us_foreign_policy|5": {
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},
"harness|hendrycksTest-virology|5": {
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"harness|hendrycksTest-world_religions|5": {
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"acc_stderr": 0.033773102522091945,
"acc_norm": 0.2631578947368421,
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"harness|truthfulqa:mc|0": {
"mc1": 0.24357405140758873,
"mc1_stderr": 0.015026354824910782,
"mc2": NaN,
"mc2_stderr": NaN
},
"harness|winogrande|5": {
"acc": 0.4980268350434096,
"acc_stderr": 0.014052376259225632
},
"harness|gsm8k|5": {
"acc": 0.0,
"acc_stderr": 0.0
}
}
```
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
[More Information Needed]
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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#### Who are the source data producers?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
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### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
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#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
[More Information Needed]
#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
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## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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### Recommendations
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shidowake/glaive-code-assistant-v1-sharegpt-format_split_14 | ---
dataset_info:
features:
- name: conversations
list:
- name: from
dtype: string
- name: value
dtype: string
splits:
- name: train
num_bytes: 10503837.603832223
num_examples: 6805
download_size: 5130529
dataset_size: 10503837.603832223
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
open-llm-leaderboard/details_SUSTech__SUS-Chat-72B | ---
pretty_name: Evaluation run of SUSTech/SUS-Chat-72B
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [SUSTech/SUS-Chat-72B](https://huggingface.co/SUSTech/SUS-Chat-72B) on the [Open\
\ LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 63 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the aggregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_SUSTech__SUS-Chat-72B\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-12-30T08:38:52.255652](https://huggingface.co/datasets/open-llm-leaderboard/details_SUSTech__SUS-Chat-72B/blob/main/results_2023-12-30T08-38-52.255652.json)(note\
\ that their might be results for other tasks in the repos if successive evals didn't\
\ cover the same tasks. You find each in the results and the \"latest\" split for\
\ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.7531471665521513,\n\
\ \"acc_stderr\": 0.028005234629175594,\n \"acc_norm\": 0.7666170688561996,\n\
\ \"acc_norm_stderr\": 0.028617434882601496,\n \"mc1\": 0.44063647490820074,\n\
\ \"mc1_stderr\": 0.017379697555437446,\n \"mc2\": 0.6026834780213507,\n\
\ \"mc2_stderr\": 0.014913414941903928\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.6373720136518771,\n \"acc_stderr\": 0.014049106564955002,\n\
\ \"acc_norm\": 0.6629692832764505,\n \"acc_norm_stderr\": 0.013813476652902274\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6585341565425215,\n\
\ \"acc_stderr\": 0.004732322172153752,\n \"acc_norm\": 0.849631547500498,\n\
\ \"acc_norm_stderr\": 0.0035670171422264854\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.42,\n \"acc_stderr\": 0.049604496374885836,\n \
\ \"acc_norm\": 0.42,\n \"acc_norm_stderr\": 0.049604496374885836\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.725925925925926,\n\
\ \"acc_stderr\": 0.038532548365520045,\n \"acc_norm\": 0.725925925925926,\n\
\ \"acc_norm_stderr\": 0.038532548365520045\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.868421052631579,\n \"acc_stderr\": 0.027508689533549915,\n\
\ \"acc_norm\": 0.868421052631579,\n \"acc_norm_stderr\": 0.027508689533549915\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.8,\n\
\ \"acc_stderr\": 0.040201512610368445,\n \"acc_norm\": 0.8,\n \
\ \"acc_norm_stderr\": 0.040201512610368445\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.8301886792452831,\n \"acc_stderr\": 0.02310839379984133,\n\
\ \"acc_norm\": 0.8301886792452831,\n \"acc_norm_stderr\": 0.02310839379984133\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.8958333333333334,\n\
\ \"acc_stderr\": 0.025545239210256917,\n \"acc_norm\": 0.8958333333333334,\n\
\ \"acc_norm_stderr\": 0.025545239210256917\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.54,\n \"acc_stderr\": 0.05009082659620333,\n \
\ \"acc_norm\": 0.54,\n \"acc_norm_stderr\": 0.05009082659620333\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\
: 0.61,\n \"acc_stderr\": 0.04902071300001975,\n \"acc_norm\": 0.61,\n\
\ \"acc_norm_stderr\": 0.04902071300001975\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.44,\n \"acc_stderr\": 0.04988876515698589,\n \
\ \"acc_norm\": 0.44,\n \"acc_norm_stderr\": 0.04988876515698589\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.7514450867052023,\n\
\ \"acc_stderr\": 0.03295304696818317,\n \"acc_norm\": 0.7514450867052023,\n\
\ \"acc_norm_stderr\": 0.03295304696818317\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.5588235294117647,\n \"acc_stderr\": 0.049406356306056595,\n\
\ \"acc_norm\": 0.5588235294117647,\n \"acc_norm_stderr\": 0.049406356306056595\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.82,\n \"acc_stderr\": 0.03861229196653695,\n \"acc_norm\": 0.82,\n\
\ \"acc_norm_stderr\": 0.03861229196653695\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.7872340425531915,\n \"acc_stderr\": 0.02675439134803977,\n\
\ \"acc_norm\": 0.7872340425531915,\n \"acc_norm_stderr\": 0.02675439134803977\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.6052631578947368,\n\
\ \"acc_stderr\": 0.045981880578165414,\n \"acc_norm\": 0.6052631578947368,\n\
\ \"acc_norm_stderr\": 0.045981880578165414\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.8,\n \"acc_stderr\": 0.03333333333333329,\n \
\ \"acc_norm\": 0.8,\n \"acc_norm_stderr\": 0.03333333333333329\n },\n\
\ \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\": 0.671957671957672,\n\
\ \"acc_stderr\": 0.024180497164376896,\n \"acc_norm\": 0.671957671957672,\n\
\ \"acc_norm_stderr\": 0.024180497164376896\n },\n \"harness|hendrycksTest-formal_logic|5\"\
: {\n \"acc\": 0.5555555555555556,\n \"acc_stderr\": 0.04444444444444449,\n\
\ \"acc_norm\": 0.5555555555555556,\n \"acc_norm_stderr\": 0.04444444444444449\n\
\ },\n \"harness|hendrycksTest-global_facts|5\": {\n \"acc\": 0.49,\n\
\ \"acc_stderr\": 0.05024183937956912,\n \"acc_norm\": 0.49,\n \
\ \"acc_norm_stderr\": 0.05024183937956912\n },\n \"harness|hendrycksTest-high_school_biology|5\"\
: {\n \"acc\": 0.8870967741935484,\n \"acc_stderr\": 0.01800360332586361,\n\
\ \"acc_norm\": 0.8870967741935484,\n \"acc_norm_stderr\": 0.01800360332586361\n\
\ },\n \"harness|hendrycksTest-high_school_chemistry|5\": {\n \"acc\"\
: 0.6798029556650246,\n \"acc_stderr\": 0.032826493853041504,\n \"\
acc_norm\": 0.6798029556650246,\n \"acc_norm_stderr\": 0.032826493853041504\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.84,\n \"acc_stderr\": 0.03684529491774709,\n \"acc_norm\"\
: 0.84,\n \"acc_norm_stderr\": 0.03684529491774709\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.8545454545454545,\n \"acc_stderr\": 0.027530196355066584,\n\
\ \"acc_norm\": 0.8545454545454545,\n \"acc_norm_stderr\": 0.027530196355066584\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.9292929292929293,\n \"acc_stderr\": 0.01826310542019951,\n \"\
acc_norm\": 0.9292929292929293,\n \"acc_norm_stderr\": 0.01826310542019951\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.9792746113989638,\n \"acc_stderr\": 0.010281417011909046,\n\
\ \"acc_norm\": 0.9792746113989638,\n \"acc_norm_stderr\": 0.010281417011909046\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.8205128205128205,\n \"acc_stderr\": 0.019457390787681786,\n\
\ \"acc_norm\": 0.8205128205128205,\n \"acc_norm_stderr\": 0.019457390787681786\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.45185185185185184,\n \"acc_stderr\": 0.030343862998512636,\n \
\ \"acc_norm\": 0.45185185185185184,\n \"acc_norm_stderr\": 0.030343862998512636\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.8529411764705882,\n \"acc_stderr\": 0.023005459446673957,\n\
\ \"acc_norm\": 0.8529411764705882,\n \"acc_norm_stderr\": 0.023005459446673957\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.5629139072847682,\n \"acc_stderr\": 0.040500357222306355,\n \"\
acc_norm\": 0.5629139072847682,\n \"acc_norm_stderr\": 0.040500357222306355\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.9247706422018349,\n \"acc_stderr\": 0.011308662537571746,\n \"\
acc_norm\": 0.9247706422018349,\n \"acc_norm_stderr\": 0.011308662537571746\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.6481481481481481,\n \"acc_stderr\": 0.032568505702936464,\n \"\
acc_norm\": 0.6481481481481481,\n \"acc_norm_stderr\": 0.032568505702936464\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.9166666666666666,\n \"acc_stderr\": 0.019398452135813905,\n \"\
acc_norm\": 0.9166666666666666,\n \"acc_norm_stderr\": 0.019398452135813905\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.9029535864978903,\n \"acc_stderr\": 0.019269323025640266,\n \
\ \"acc_norm\": 0.9029535864978903,\n \"acc_norm_stderr\": 0.019269323025640266\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.8116591928251121,\n\
\ \"acc_stderr\": 0.026241132996407256,\n \"acc_norm\": 0.8116591928251121,\n\
\ \"acc_norm_stderr\": 0.026241132996407256\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.8854961832061069,\n \"acc_stderr\": 0.027927473753597446,\n\
\ \"acc_norm\": 0.8854961832061069,\n \"acc_norm_stderr\": 0.027927473753597446\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.8842975206611571,\n \"acc_stderr\": 0.029199802455622814,\n \"\
acc_norm\": 0.8842975206611571,\n \"acc_norm_stderr\": 0.029199802455622814\n\
\ },\n \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.8796296296296297,\n\
\ \"acc_stderr\": 0.031457038543062504,\n \"acc_norm\": 0.8796296296296297,\n\
\ \"acc_norm_stderr\": 0.031457038543062504\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.852760736196319,\n \"acc_stderr\": 0.027839915278339653,\n\
\ \"acc_norm\": 0.852760736196319,\n \"acc_norm_stderr\": 0.027839915278339653\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.6339285714285714,\n\
\ \"acc_stderr\": 0.04572372358737431,\n \"acc_norm\": 0.6339285714285714,\n\
\ \"acc_norm_stderr\": 0.04572372358737431\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.8543689320388349,\n \"acc_stderr\": 0.034926064766237906,\n\
\ \"acc_norm\": 0.8543689320388349,\n \"acc_norm_stderr\": 0.034926064766237906\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.9444444444444444,\n\
\ \"acc_stderr\": 0.015006312806446908,\n \"acc_norm\": 0.9444444444444444,\n\
\ \"acc_norm_stderr\": 0.015006312806446908\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.83,\n \"acc_stderr\": 0.0377525168068637,\n \
\ \"acc_norm\": 0.83,\n \"acc_norm_stderr\": 0.0377525168068637\n },\n\
\ \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.9233716475095786,\n\
\ \"acc_stderr\": 0.00951217069932386,\n \"acc_norm\": 0.9233716475095786,\n\
\ \"acc_norm_stderr\": 0.00951217069932386\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.8323699421965318,\n \"acc_stderr\": 0.020110579919734847,\n\
\ \"acc_norm\": 0.8323699421965318,\n \"acc_norm_stderr\": 0.020110579919734847\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.6022346368715084,\n\
\ \"acc_stderr\": 0.01636920497126299,\n \"acc_norm\": 0.6022346368715084,\n\
\ \"acc_norm_stderr\": 0.01636920497126299\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.8627450980392157,\n \"acc_stderr\": 0.019704039183859812,\n\
\ \"acc_norm\": 0.8627450980392157,\n \"acc_norm_stderr\": 0.019704039183859812\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.8263665594855305,\n\
\ \"acc_stderr\": 0.021514051585970393,\n \"acc_norm\": 0.8263665594855305,\n\
\ \"acc_norm_stderr\": 0.021514051585970393\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.8703703703703703,\n \"acc_stderr\": 0.018689725721062065,\n\
\ \"acc_norm\": 0.8703703703703703,\n \"acc_norm_stderr\": 0.018689725721062065\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.6524822695035462,\n \"acc_stderr\": 0.02840662780959095,\n \
\ \"acc_norm\": 0.6524822695035462,\n \"acc_norm_stderr\": 0.02840662780959095\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.6121251629726207,\n\
\ \"acc_stderr\": 0.012444998309675633,\n \"acc_norm\": 0.6121251629726207,\n\
\ \"acc_norm_stderr\": 0.012444998309675633\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.8345588235294118,\n \"acc_stderr\": 0.022571771025494743,\n\
\ \"acc_norm\": 0.8345588235294118,\n \"acc_norm_stderr\": 0.022571771025494743\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.8120915032679739,\n \"acc_stderr\": 0.01580356573677669,\n \
\ \"acc_norm\": 0.8120915032679739,\n \"acc_norm_stderr\": 0.01580356573677669\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.7909090909090909,\n\
\ \"acc_stderr\": 0.03895091015724136,\n \"acc_norm\": 0.7909090909090909,\n\
\ \"acc_norm_stderr\": 0.03895091015724136\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.8122448979591836,\n \"acc_stderr\": 0.0250002560395462,\n\
\ \"acc_norm\": 0.8122448979591836,\n \"acc_norm_stderr\": 0.0250002560395462\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.900497512437811,\n\
\ \"acc_stderr\": 0.0211662163046594,\n \"acc_norm\": 0.900497512437811,\n\
\ \"acc_norm_stderr\": 0.0211662163046594\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.95,\n \"acc_stderr\": 0.02190429135575904,\n \
\ \"acc_norm\": 0.95,\n \"acc_norm_stderr\": 0.02190429135575904\n \
\ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5602409638554217,\n\
\ \"acc_stderr\": 0.03864139923699122,\n \"acc_norm\": 0.5602409638554217,\n\
\ \"acc_norm_stderr\": 0.03864139923699122\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.8771929824561403,\n \"acc_stderr\": 0.02517298435015577,\n\
\ \"acc_norm\": 0.8771929824561403,\n \"acc_norm_stderr\": 0.02517298435015577\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.44063647490820074,\n\
\ \"mc1_stderr\": 0.017379697555437446,\n \"mc2\": 0.6026834780213507,\n\
\ \"mc2_stderr\": 0.014913414941903928\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.8342541436464088,\n \"acc_stderr\": 0.010450899545370637\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.09401061410159212,\n \
\ \"acc_stderr\": 0.008038819818872465\n }\n}\n```"
repo_url: https://huggingface.co/SUSTech/SUS-Chat-72B
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|arc:challenge|25_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|gsm8k|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hellaswag|10_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-12-30T08-38-52.255652.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-12-30T08-38-52.255652.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- '**/details_harness|winogrande|5_2023-12-30T08-38-52.255652.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-12-30T08-38-52.255652.parquet'
- config_name: results
data_files:
- split: 2023_12_30T08_38_52.255652
path:
- results_2023-12-30T08-38-52.255652.parquet
- split: latest
path:
- results_2023-12-30T08-38-52.255652.parquet
---
# Dataset Card for Evaluation run of SUSTech/SUS-Chat-72B
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [SUSTech/SUS-Chat-72B](https://huggingface.co/SUSTech/SUS-Chat-72B) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_SUSTech__SUS-Chat-72B",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-12-30T08:38:52.255652](https://huggingface.co/datasets/open-llm-leaderboard/details_SUSTech__SUS-Chat-72B/blob/main/results_2023-12-30T08-38-52.255652.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"acc": 0.7531471665521513,
"acc_stderr": 0.028005234629175594,
"acc_norm": 0.7666170688561996,
"acc_norm_stderr": 0.028617434882601496,
"mc1": 0.44063647490820074,
"mc1_stderr": 0.017379697555437446,
"mc2": 0.6026834780213507,
"mc2_stderr": 0.014913414941903928
},
"harness|arc:challenge|25": {
"acc": 0.6373720136518771,
"acc_stderr": 0.014049106564955002,
"acc_norm": 0.6629692832764505,
"acc_norm_stderr": 0.013813476652902274
},
"harness|hellaswag|10": {
"acc": 0.6585341565425215,
"acc_stderr": 0.004732322172153752,
"acc_norm": 0.849631547500498,
"acc_norm_stderr": 0.0035670171422264854
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.42,
"acc_stderr": 0.049604496374885836,
"acc_norm": 0.42,
"acc_norm_stderr": 0.049604496374885836
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.725925925925926,
"acc_stderr": 0.038532548365520045,
"acc_norm": 0.725925925925926,
"acc_norm_stderr": 0.038532548365520045
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.868421052631579,
"acc_stderr": 0.027508689533549915,
"acc_norm": 0.868421052631579,
"acc_norm_stderr": 0.027508689533549915
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.8,
"acc_stderr": 0.040201512610368445,
"acc_norm": 0.8,
"acc_norm_stderr": 0.040201512610368445
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.8301886792452831,
"acc_stderr": 0.02310839379984133,
"acc_norm": 0.8301886792452831,
"acc_norm_stderr": 0.02310839379984133
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.8958333333333334,
"acc_stderr": 0.025545239210256917,
"acc_norm": 0.8958333333333334,
"acc_norm_stderr": 0.025545239210256917
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.54,
"acc_stderr": 0.05009082659620333,
"acc_norm": 0.54,
"acc_norm_stderr": 0.05009082659620333
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.61,
"acc_stderr": 0.04902071300001975,
"acc_norm": 0.61,
"acc_norm_stderr": 0.04902071300001975
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.44,
"acc_stderr": 0.04988876515698589,
"acc_norm": 0.44,
"acc_norm_stderr": 0.04988876515698589
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.7514450867052023,
"acc_stderr": 0.03295304696818317,
"acc_norm": 0.7514450867052023,
"acc_norm_stderr": 0.03295304696818317
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.5588235294117647,
"acc_stderr": 0.049406356306056595,
"acc_norm": 0.5588235294117647,
"acc_norm_stderr": 0.049406356306056595
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.82,
"acc_stderr": 0.03861229196653695,
"acc_norm": 0.82,
"acc_norm_stderr": 0.03861229196653695
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.7872340425531915,
"acc_stderr": 0.02675439134803977,
"acc_norm": 0.7872340425531915,
"acc_norm_stderr": 0.02675439134803977
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.6052631578947368,
"acc_stderr": 0.045981880578165414,
"acc_norm": 0.6052631578947368,
"acc_norm_stderr": 0.045981880578165414
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.8,
"acc_stderr": 0.03333333333333329,
"acc_norm": 0.8,
"acc_norm_stderr": 0.03333333333333329
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.671957671957672,
"acc_stderr": 0.024180497164376896,
"acc_norm": 0.671957671957672,
"acc_norm_stderr": 0.024180497164376896
},
"harness|hendrycksTest-formal_logic|5": {
"acc": 0.5555555555555556,
"acc_stderr": 0.04444444444444449,
"acc_norm": 0.5555555555555556,
"acc_norm_stderr": 0.04444444444444449
},
"harness|hendrycksTest-global_facts|5": {
"acc": 0.49,
"acc_stderr": 0.05024183937956912,
"acc_norm": 0.49,
"acc_norm_stderr": 0.05024183937956912
},
"harness|hendrycksTest-high_school_biology|5": {
"acc": 0.8870967741935484,
"acc_stderr": 0.01800360332586361,
"acc_norm": 0.8870967741935484,
"acc_norm_stderr": 0.01800360332586361
},
"harness|hendrycksTest-high_school_chemistry|5": {
"acc": 0.6798029556650246,
"acc_stderr": 0.032826493853041504,
"acc_norm": 0.6798029556650246,
"acc_norm_stderr": 0.032826493853041504
},
"harness|hendrycksTest-high_school_computer_science|5": {
"acc": 0.84,
"acc_stderr": 0.03684529491774709,
"acc_norm": 0.84,
"acc_norm_stderr": 0.03684529491774709
},
"harness|hendrycksTest-high_school_european_history|5": {
"acc": 0.8545454545454545,
"acc_stderr": 0.027530196355066584,
"acc_norm": 0.8545454545454545,
"acc_norm_stderr": 0.027530196355066584
},
"harness|hendrycksTest-high_school_geography|5": {
"acc": 0.9292929292929293,
"acc_stderr": 0.01826310542019951,
"acc_norm": 0.9292929292929293,
"acc_norm_stderr": 0.01826310542019951
},
"harness|hendrycksTest-high_school_government_and_politics|5": {
"acc": 0.9792746113989638,
"acc_stderr": 0.010281417011909046,
"acc_norm": 0.9792746113989638,
"acc_norm_stderr": 0.010281417011909046
},
"harness|hendrycksTest-high_school_macroeconomics|5": {
"acc": 0.8205128205128205,
"acc_stderr": 0.019457390787681786,
"acc_norm": 0.8205128205128205,
"acc_norm_stderr": 0.019457390787681786
},
"harness|hendrycksTest-high_school_mathematics|5": {
"acc": 0.45185185185185184,
"acc_stderr": 0.030343862998512636,
"acc_norm": 0.45185185185185184,
"acc_norm_stderr": 0.030343862998512636
},
"harness|hendrycksTest-high_school_microeconomics|5": {
"acc": 0.8529411764705882,
"acc_stderr": 0.023005459446673957,
"acc_norm": 0.8529411764705882,
"acc_norm_stderr": 0.023005459446673957
},
"harness|hendrycksTest-high_school_physics|5": {
"acc": 0.5629139072847682,
"acc_stderr": 0.040500357222306355,
"acc_norm": 0.5629139072847682,
"acc_norm_stderr": 0.040500357222306355
},
"harness|hendrycksTest-high_school_psychology|5": {
"acc": 0.9247706422018349,
"acc_stderr": 0.011308662537571746,
"acc_norm": 0.9247706422018349,
"acc_norm_stderr": 0.011308662537571746
},
"harness|hendrycksTest-high_school_statistics|5": {
"acc": 0.6481481481481481,
"acc_stderr": 0.032568505702936464,
"acc_norm": 0.6481481481481481,
"acc_norm_stderr": 0.032568505702936464
},
"harness|hendrycksTest-high_school_us_history|5": {
"acc": 0.9166666666666666,
"acc_stderr": 0.019398452135813905,
"acc_norm": 0.9166666666666666,
"acc_norm_stderr": 0.019398452135813905
},
"harness|hendrycksTest-high_school_world_history|5": {
"acc": 0.9029535864978903,
"acc_stderr": 0.019269323025640266,
"acc_norm": 0.9029535864978903,
"acc_norm_stderr": 0.019269323025640266
},
"harness|hendrycksTest-human_aging|5": {
"acc": 0.8116591928251121,
"acc_stderr": 0.026241132996407256,
"acc_norm": 0.8116591928251121,
"acc_norm_stderr": 0.026241132996407256
},
"harness|hendrycksTest-human_sexuality|5": {
"acc": 0.8854961832061069,
"acc_stderr": 0.027927473753597446,
"acc_norm": 0.8854961832061069,
"acc_norm_stderr": 0.027927473753597446
},
"harness|hendrycksTest-international_law|5": {
"acc": 0.8842975206611571,
"acc_stderr": 0.029199802455622814,
"acc_norm": 0.8842975206611571,
"acc_norm_stderr": 0.029199802455622814
},
"harness|hendrycksTest-jurisprudence|5": {
"acc": 0.8796296296296297,
"acc_stderr": 0.031457038543062504,
"acc_norm": 0.8796296296296297,
"acc_norm_stderr": 0.031457038543062504
},
"harness|hendrycksTest-logical_fallacies|5": {
"acc": 0.852760736196319,
"acc_stderr": 0.027839915278339653,
"acc_norm": 0.852760736196319,
"acc_norm_stderr": 0.027839915278339653
},
"harness|hendrycksTest-machine_learning|5": {
"acc": 0.6339285714285714,
"acc_stderr": 0.04572372358737431,
"acc_norm": 0.6339285714285714,
"acc_norm_stderr": 0.04572372358737431
},
"harness|hendrycksTest-management|5": {
"acc": 0.8543689320388349,
"acc_stderr": 0.034926064766237906,
"acc_norm": 0.8543689320388349,
"acc_norm_stderr": 0.034926064766237906
},
"harness|hendrycksTest-marketing|5": {
"acc": 0.9444444444444444,
"acc_stderr": 0.015006312806446908,
"acc_norm": 0.9444444444444444,
"acc_norm_stderr": 0.015006312806446908
},
"harness|hendrycksTest-medical_genetics|5": {
"acc": 0.83,
"acc_stderr": 0.0377525168068637,
"acc_norm": 0.83,
"acc_norm_stderr": 0.0377525168068637
},
"harness|hendrycksTest-miscellaneous|5": {
"acc": 0.9233716475095786,
"acc_stderr": 0.00951217069932386,
"acc_norm": 0.9233716475095786,
"acc_norm_stderr": 0.00951217069932386
},
"harness|hendrycksTest-moral_disputes|5": {
"acc": 0.8323699421965318,
"acc_stderr": 0.020110579919734847,
"acc_norm": 0.8323699421965318,
"acc_norm_stderr": 0.020110579919734847
},
"harness|hendrycksTest-moral_scenarios|5": {
"acc": 0.6022346368715084,
"acc_stderr": 0.01636920497126299,
"acc_norm": 0.6022346368715084,
"acc_norm_stderr": 0.01636920497126299
},
"harness|hendrycksTest-nutrition|5": {
"acc": 0.8627450980392157,
"acc_stderr": 0.019704039183859812,
"acc_norm": 0.8627450980392157,
"acc_norm_stderr": 0.019704039183859812
},
"harness|hendrycksTest-philosophy|5": {
"acc": 0.8263665594855305,
"acc_stderr": 0.021514051585970393,
"acc_norm": 0.8263665594855305,
"acc_norm_stderr": 0.021514051585970393
},
"harness|hendrycksTest-prehistory|5": {
"acc": 0.8703703703703703,
"acc_stderr": 0.018689725721062065,
"acc_norm": 0.8703703703703703,
"acc_norm_stderr": 0.018689725721062065
},
"harness|hendrycksTest-professional_accounting|5": {
"acc": 0.6524822695035462,
"acc_stderr": 0.02840662780959095,
"acc_norm": 0.6524822695035462,
"acc_norm_stderr": 0.02840662780959095
},
"harness|hendrycksTest-professional_law|5": {
"acc": 0.6121251629726207,
"acc_stderr": 0.012444998309675633,
"acc_norm": 0.6121251629726207,
"acc_norm_stderr": 0.012444998309675633
},
"harness|hendrycksTest-professional_medicine|5": {
"acc": 0.8345588235294118,
"acc_stderr": 0.022571771025494743,
"acc_norm": 0.8345588235294118,
"acc_norm_stderr": 0.022571771025494743
},
"harness|hendrycksTest-professional_psychology|5": {
"acc": 0.8120915032679739,
"acc_stderr": 0.01580356573677669,
"acc_norm": 0.8120915032679739,
"acc_norm_stderr": 0.01580356573677669
},
"harness|hendrycksTest-public_relations|5": {
"acc": 0.7909090909090909,
"acc_stderr": 0.03895091015724136,
"acc_norm": 0.7909090909090909,
"acc_norm_stderr": 0.03895091015724136
},
"harness|hendrycksTest-security_studies|5": {
"acc": 0.8122448979591836,
"acc_stderr": 0.0250002560395462,
"acc_norm": 0.8122448979591836,
"acc_norm_stderr": 0.0250002560395462
},
"harness|hendrycksTest-sociology|5": {
"acc": 0.900497512437811,
"acc_stderr": 0.0211662163046594,
"acc_norm": 0.900497512437811,
"acc_norm_stderr": 0.0211662163046594
},
"harness|hendrycksTest-us_foreign_policy|5": {
"acc": 0.95,
"acc_stderr": 0.02190429135575904,
"acc_norm": 0.95,
"acc_norm_stderr": 0.02190429135575904
},
"harness|hendrycksTest-virology|5": {
"acc": 0.5602409638554217,
"acc_stderr": 0.03864139923699122,
"acc_norm": 0.5602409638554217,
"acc_norm_stderr": 0.03864139923699122
},
"harness|hendrycksTest-world_religions|5": {
"acc": 0.8771929824561403,
"acc_stderr": 0.02517298435015577,
"acc_norm": 0.8771929824561403,
"acc_norm_stderr": 0.02517298435015577
},
"harness|truthfulqa:mc|0": {
"mc1": 0.44063647490820074,
"mc1_stderr": 0.017379697555437446,
"mc2": 0.6026834780213507,
"mc2_stderr": 0.014913414941903928
},
"harness|winogrande|5": {
"acc": 0.8342541436464088,
"acc_stderr": 0.010450899545370637
},
"harness|gsm8k|5": {
"acc": 0.09401061410159212,
"acc_stderr": 0.008038819818872465
}
}
```
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
[More Information Needed]
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
[More Information Needed]
#### Who are the source data producers?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
[More Information Needed]
### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
[More Information Needed]
#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
[More Information Needed]
#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
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## Dataset Card Authors [optional]
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## Dataset Card Contact
[More Information Needed] |
liuyanchen1015/MULTI_VALUE_qqp_em_obj_pronoun | ---
dataset_info:
features:
- name: question1
dtype: string
- name: question2
dtype: string
- name: label
dtype: int64
- name: idx
dtype: int64
- name: value_score
dtype: int64
splits:
- name: dev
num_bytes: 278153
num_examples: 1330
- name: test
num_bytes: 2812194
num_examples: 13505
- name: train
num_bytes: 2618023
num_examples: 12240
download_size: 3565928
dataset_size: 5708370
---
# Dataset Card for "MULTI_VALUE_qqp_em_obj_pronoun"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
AdapterOcean/data-standardized_cluster_7_alpaca | ---
dataset_info:
features:
- name: input
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 2673983
num_examples: 1212
download_size: 1078785
dataset_size: 2673983
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "data-standardized_cluster_7_alpaca"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
nhantruongcse/summary-vietnamese-news-token-TFtest_vit5_large_vietnews | ---
dataset_info:
features:
- name: Content
dtype: string
- name: Summary
dtype: string
- name: input_ids
sequence: int32
- name: attention_mask
sequence: int8
- name: labels
sequence: int64
splits:
- name: train
num_bytes: 61956745
num_examples: 8229
download_size: 27478662
dataset_size: 61956745
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
Cacau/wylarllysBase | ---
license: apache-2.0
---
|
open-llm-leaderboard/details_CorticalStack__pastiche-crown-clown-7b-dare-dpo | ---
pretty_name: Evaluation run of CorticalStack/pastiche-crown-clown-7b-dare-dpo
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [CorticalStack/pastiche-crown-clown-7b-dare-dpo](https://huggingface.co/CorticalStack/pastiche-crown-clown-7b-dare-dpo)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 63 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the aggregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_CorticalStack__pastiche-crown-clown-7b-dare-dpo\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2024-03-02T10:25:24.456289](https://huggingface.co/datasets/open-llm-leaderboard/details_CorticalStack__pastiche-crown-clown-7b-dare-dpo/blob/main/results_2024-03-02T10-25-24.456289.json)(note\
\ that their might be results for other tasks in the repos if successive evals didn't\
\ cover the same tasks. You find each in the results and the \"latest\" split for\
\ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.6513423294131513,\n\
\ \"acc_stderr\": 0.032196626705938945,\n \"acc_norm\": 0.6507091505416488,\n\
\ \"acc_norm_stderr\": 0.03287257709722307,\n \"mc1\": 0.6303549571603427,\n\
\ \"mc1_stderr\": 0.01689818070697388,\n \"mc2\": 0.7879954644230095,\n\
\ \"mc2_stderr\": 0.013634507690257524\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.7081911262798635,\n \"acc_stderr\": 0.013284525292403511,\n\
\ \"acc_norm\": 0.7278156996587031,\n \"acc_norm_stderr\": 0.013006600406423702\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.7135032861979685,\n\
\ \"acc_stderr\": 0.004512002459757957,\n \"acc_norm\": 0.8914558852818164,\n\
\ \"acc_norm_stderr\": 0.0031043064349724637\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.34,\n \"acc_stderr\": 0.04760952285695235,\n \
\ \"acc_norm\": 0.34,\n \"acc_norm_stderr\": 0.04760952285695235\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.6444444444444445,\n\
\ \"acc_stderr\": 0.04135176749720385,\n \"acc_norm\": 0.6444444444444445,\n\
\ \"acc_norm_stderr\": 0.04135176749720385\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.7171052631578947,\n \"acc_stderr\": 0.03665349695640767,\n\
\ \"acc_norm\": 0.7171052631578947,\n \"acc_norm_stderr\": 0.03665349695640767\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.63,\n\
\ \"acc_stderr\": 0.04852365870939099,\n \"acc_norm\": 0.63,\n \
\ \"acc_norm_stderr\": 0.04852365870939099\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.6792452830188679,\n \"acc_stderr\": 0.02872750295788027,\n\
\ \"acc_norm\": 0.6792452830188679,\n \"acc_norm_stderr\": 0.02872750295788027\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.7569444444444444,\n\
\ \"acc_stderr\": 0.0358687928008034,\n \"acc_norm\": 0.7569444444444444,\n\
\ \"acc_norm_stderr\": 0.0358687928008034\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.51,\n \"acc_stderr\": 0.05024183937956912,\n \
\ \"acc_norm\": 0.51,\n \"acc_norm_stderr\": 0.05024183937956912\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\
: 0.57,\n \"acc_stderr\": 0.04975698519562428,\n \"acc_norm\": 0.57,\n\
\ \"acc_norm_stderr\": 0.04975698519562428\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.32,\n \"acc_stderr\": 0.046882617226215034,\n \
\ \"acc_norm\": 0.32,\n \"acc_norm_stderr\": 0.046882617226215034\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.630057803468208,\n\
\ \"acc_stderr\": 0.0368122963339432,\n \"acc_norm\": 0.630057803468208,\n\
\ \"acc_norm_stderr\": 0.0368122963339432\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.4215686274509804,\n \"acc_stderr\": 0.049135952012744975,\n\
\ \"acc_norm\": 0.4215686274509804,\n \"acc_norm_stderr\": 0.049135952012744975\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.73,\n \"acc_stderr\": 0.044619604333847394,\n \"acc_norm\": 0.73,\n\
\ \"acc_norm_stderr\": 0.044619604333847394\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.5531914893617021,\n \"acc_stderr\": 0.0325005368436584,\n\
\ \"acc_norm\": 0.5531914893617021,\n \"acc_norm_stderr\": 0.0325005368436584\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.47368421052631576,\n\
\ \"acc_stderr\": 0.04697085136647863,\n \"acc_norm\": 0.47368421052631576,\n\
\ \"acc_norm_stderr\": 0.04697085136647863\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.5586206896551724,\n \"acc_stderr\": 0.04137931034482757,\n\
\ \"acc_norm\": 0.5586206896551724,\n \"acc_norm_stderr\": 0.04137931034482757\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.4126984126984127,\n \"acc_stderr\": 0.02535574126305527,\n \"\
acc_norm\": 0.4126984126984127,\n \"acc_norm_stderr\": 0.02535574126305527\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.48412698412698413,\n\
\ \"acc_stderr\": 0.04469881854072606,\n \"acc_norm\": 0.48412698412698413,\n\
\ \"acc_norm_stderr\": 0.04469881854072606\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.31,\n \"acc_stderr\": 0.04648231987117316,\n \
\ \"acc_norm\": 0.31,\n \"acc_norm_stderr\": 0.04648231987117316\n \
\ },\n \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.7806451612903226,\n\
\ \"acc_stderr\": 0.023540799358723295,\n \"acc_norm\": 0.7806451612903226,\n\
\ \"acc_norm_stderr\": 0.023540799358723295\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\
: {\n \"acc\": 0.5172413793103449,\n \"acc_stderr\": 0.035158955511656986,\n\
\ \"acc_norm\": 0.5172413793103449,\n \"acc_norm_stderr\": 0.035158955511656986\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.69,\n \"acc_stderr\": 0.04648231987117316,\n \"acc_norm\"\
: 0.69,\n \"acc_norm_stderr\": 0.04648231987117316\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.7454545454545455,\n \"acc_stderr\": 0.03401506715249039,\n\
\ \"acc_norm\": 0.7454545454545455,\n \"acc_norm_stderr\": 0.03401506715249039\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.803030303030303,\n \"acc_stderr\": 0.028335609732463362,\n \"\
acc_norm\": 0.803030303030303,\n \"acc_norm_stderr\": 0.028335609732463362\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.8911917098445595,\n \"acc_stderr\": 0.022473253332768763,\n\
\ \"acc_norm\": 0.8911917098445595,\n \"acc_norm_stderr\": 0.022473253332768763\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.6692307692307692,\n \"acc_stderr\": 0.023854795680971128,\n\
\ \"acc_norm\": 0.6692307692307692,\n \"acc_norm_stderr\": 0.023854795680971128\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.3333333333333333,\n \"acc_stderr\": 0.028742040903948485,\n \
\ \"acc_norm\": 0.3333333333333333,\n \"acc_norm_stderr\": 0.028742040903948485\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.6680672268907563,\n \"acc_stderr\": 0.03058869701378364,\n \
\ \"acc_norm\": 0.6680672268907563,\n \"acc_norm_stderr\": 0.03058869701378364\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.39072847682119205,\n \"acc_stderr\": 0.03983798306659807,\n \"\
acc_norm\": 0.39072847682119205,\n \"acc_norm_stderr\": 0.03983798306659807\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.8422018348623853,\n \"acc_stderr\": 0.01563002297009244,\n \"\
acc_norm\": 0.8422018348623853,\n \"acc_norm_stderr\": 0.01563002297009244\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.5370370370370371,\n \"acc_stderr\": 0.03400603625538272,\n \"\
acc_norm\": 0.5370370370370371,\n \"acc_norm_stderr\": 0.03400603625538272\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.8480392156862745,\n \"acc_stderr\": 0.025195658428931792,\n \"\
acc_norm\": 0.8480392156862745,\n \"acc_norm_stderr\": 0.025195658428931792\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.8185654008438819,\n \"acc_stderr\": 0.02508596114457966,\n \
\ \"acc_norm\": 0.8185654008438819,\n \"acc_norm_stderr\": 0.02508596114457966\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.6860986547085202,\n\
\ \"acc_stderr\": 0.031146796482972465,\n \"acc_norm\": 0.6860986547085202,\n\
\ \"acc_norm_stderr\": 0.031146796482972465\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.7938931297709924,\n \"acc_stderr\": 0.03547771004159463,\n\
\ \"acc_norm\": 0.7938931297709924,\n \"acc_norm_stderr\": 0.03547771004159463\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.768595041322314,\n \"acc_stderr\": 0.03849856098794088,\n \"acc_norm\"\
: 0.768595041322314,\n \"acc_norm_stderr\": 0.03849856098794088\n },\n\
\ \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.7962962962962963,\n\
\ \"acc_stderr\": 0.03893542518824847,\n \"acc_norm\": 0.7962962962962963,\n\
\ \"acc_norm_stderr\": 0.03893542518824847\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.7668711656441718,\n \"acc_stderr\": 0.0332201579577674,\n\
\ \"acc_norm\": 0.7668711656441718,\n \"acc_norm_stderr\": 0.0332201579577674\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.42857142857142855,\n\
\ \"acc_stderr\": 0.04697113923010212,\n \"acc_norm\": 0.42857142857142855,\n\
\ \"acc_norm_stderr\": 0.04697113923010212\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.7669902912621359,\n \"acc_stderr\": 0.04185832598928315,\n\
\ \"acc_norm\": 0.7669902912621359,\n \"acc_norm_stderr\": 0.04185832598928315\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.8675213675213675,\n\
\ \"acc_stderr\": 0.022209309073165612,\n \"acc_norm\": 0.8675213675213675,\n\
\ \"acc_norm_stderr\": 0.022209309073165612\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.72,\n \"acc_stderr\": 0.045126085985421276,\n \
\ \"acc_norm\": 0.72,\n \"acc_norm_stderr\": 0.045126085985421276\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.8199233716475096,\n\
\ \"acc_stderr\": 0.013740797258579828,\n \"acc_norm\": 0.8199233716475096,\n\
\ \"acc_norm_stderr\": 0.013740797258579828\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.7138728323699421,\n \"acc_stderr\": 0.02433214677913413,\n\
\ \"acc_norm\": 0.7138728323699421,\n \"acc_norm_stderr\": 0.02433214677913413\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.42793296089385474,\n\
\ \"acc_stderr\": 0.01654788799741611,\n \"acc_norm\": 0.42793296089385474,\n\
\ \"acc_norm_stderr\": 0.01654788799741611\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.7189542483660131,\n \"acc_stderr\": 0.025738854797818737,\n\
\ \"acc_norm\": 0.7189542483660131,\n \"acc_norm_stderr\": 0.025738854797818737\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.684887459807074,\n\
\ \"acc_stderr\": 0.026385273703464492,\n \"acc_norm\": 0.684887459807074,\n\
\ \"acc_norm_stderr\": 0.026385273703464492\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.7376543209876543,\n \"acc_stderr\": 0.024477222856135114,\n\
\ \"acc_norm\": 0.7376543209876543,\n \"acc_norm_stderr\": 0.024477222856135114\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.5035460992907801,\n \"acc_stderr\": 0.02982674915328092,\n \
\ \"acc_norm\": 0.5035460992907801,\n \"acc_norm_stderr\": 0.02982674915328092\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.4654498044328553,\n\
\ \"acc_stderr\": 0.012739711554045704,\n \"acc_norm\": 0.4654498044328553,\n\
\ \"acc_norm_stderr\": 0.012739711554045704\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.6654411764705882,\n \"acc_stderr\": 0.0286619962023353,\n\
\ \"acc_norm\": 0.6654411764705882,\n \"acc_norm_stderr\": 0.0286619962023353\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.6699346405228758,\n \"acc_stderr\": 0.019023726160724553,\n \
\ \"acc_norm\": 0.6699346405228758,\n \"acc_norm_stderr\": 0.019023726160724553\n\
\ },\n \"harness|hendrycksTest-public_relations|5\": {\n \"acc\": 0.6818181818181818,\n\
\ \"acc_stderr\": 0.044612721759105085,\n \"acc_norm\": 0.6818181818181818,\n\
\ \"acc_norm_stderr\": 0.044612721759105085\n },\n \"harness|hendrycksTest-security_studies|5\"\
: {\n \"acc\": 0.7346938775510204,\n \"acc_stderr\": 0.028263889943784596,\n\
\ \"acc_norm\": 0.7346938775510204,\n \"acc_norm_stderr\": 0.028263889943784596\n\
\ },\n \"harness|hendrycksTest-sociology|5\": {\n \"acc\": 0.8308457711442786,\n\
\ \"acc_stderr\": 0.026508590656233268,\n \"acc_norm\": 0.8308457711442786,\n\
\ \"acc_norm_stderr\": 0.026508590656233268\n },\n \"harness|hendrycksTest-us_foreign_policy|5\"\
: {\n \"acc\": 0.85,\n \"acc_stderr\": 0.03588702812826371,\n \
\ \"acc_norm\": 0.85,\n \"acc_norm_stderr\": 0.03588702812826371\n \
\ },\n \"harness|hendrycksTest-virology|5\": {\n \"acc\": 0.5542168674698795,\n\
\ \"acc_stderr\": 0.03869543323472101,\n \"acc_norm\": 0.5542168674698795,\n\
\ \"acc_norm_stderr\": 0.03869543323472101\n },\n \"harness|hendrycksTest-world_religions|5\"\
: {\n \"acc\": 0.8421052631578947,\n \"acc_stderr\": 0.02796678585916089,\n\
\ \"acc_norm\": 0.8421052631578947,\n \"acc_norm_stderr\": 0.02796678585916089\n\
\ },\n \"harness|truthfulqa:mc|0\": {\n \"mc1\": 0.6303549571603427,\n\
\ \"mc1_stderr\": 0.01689818070697388,\n \"mc2\": 0.7879954644230095,\n\
\ \"mc2_stderr\": 0.013634507690257524\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.8484609313338595,\n \"acc_stderr\": 0.010077698907571776\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.689158453373768,\n \
\ \"acc_stderr\": 0.012748860507777725\n }\n}\n```"
repo_url: https://huggingface.co/CorticalStack/pastiche-crown-clown-7b-dare-dpo
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|arc:challenge|25_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|gsm8k|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hellaswag|10_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-03-02T10-25-24.456289.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-management|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-virology|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|truthfulqa:mc|0_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2024-03-02T10-25-24.456289.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- '**/details_harness|winogrande|5_2024-03-02T10-25-24.456289.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2024-03-02T10-25-24.456289.parquet'
- config_name: results
data_files:
- split: 2024_03_02T10_25_24.456289
path:
- results_2024-03-02T10-25-24.456289.parquet
- split: latest
path:
- results_2024-03-02T10-25-24.456289.parquet
---
# Dataset Card for Evaluation run of CorticalStack/pastiche-crown-clown-7b-dare-dpo
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [CorticalStack/pastiche-crown-clown-7b-dare-dpo](https://huggingface.co/CorticalStack/pastiche-crown-clown-7b-dare-dpo) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_CorticalStack__pastiche-crown-clown-7b-dare-dpo",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-03-02T10:25:24.456289](https://huggingface.co/datasets/open-llm-leaderboard/details_CorticalStack__pastiche-crown-clown-7b-dare-dpo/blob/main/results_2024-03-02T10-25-24.456289.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"acc": 0.6513423294131513,
"acc_stderr": 0.032196626705938945,
"acc_norm": 0.6507091505416488,
"acc_norm_stderr": 0.03287257709722307,
"mc1": 0.6303549571603427,
"mc1_stderr": 0.01689818070697388,
"mc2": 0.7879954644230095,
"mc2_stderr": 0.013634507690257524
},
"harness|arc:challenge|25": {
"acc": 0.7081911262798635,
"acc_stderr": 0.013284525292403511,
"acc_norm": 0.7278156996587031,
"acc_norm_stderr": 0.013006600406423702
},
"harness|hellaswag|10": {
"acc": 0.7135032861979685,
"acc_stderr": 0.004512002459757957,
"acc_norm": 0.8914558852818164,
"acc_norm_stderr": 0.0031043064349724637
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.34,
"acc_stderr": 0.04760952285695235,
"acc_norm": 0.34,
"acc_norm_stderr": 0.04760952285695235
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.6444444444444445,
"acc_stderr": 0.04135176749720385,
"acc_norm": 0.6444444444444445,
"acc_norm_stderr": 0.04135176749720385
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.7171052631578947,
"acc_stderr": 0.03665349695640767,
"acc_norm": 0.7171052631578947,
"acc_norm_stderr": 0.03665349695640767
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.63,
"acc_stderr": 0.04852365870939099,
"acc_norm": 0.63,
"acc_norm_stderr": 0.04852365870939099
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.6792452830188679,
"acc_stderr": 0.02872750295788027,
"acc_norm": 0.6792452830188679,
"acc_norm_stderr": 0.02872750295788027
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.7569444444444444,
"acc_stderr": 0.0358687928008034,
"acc_norm": 0.7569444444444444,
"acc_norm_stderr": 0.0358687928008034
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.51,
"acc_stderr": 0.05024183937956912,
"acc_norm": 0.51,
"acc_norm_stderr": 0.05024183937956912
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.57,
"acc_stderr": 0.04975698519562428,
"acc_norm": 0.57,
"acc_norm_stderr": 0.04975698519562428
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.32,
"acc_stderr": 0.046882617226215034,
"acc_norm": 0.32,
"acc_norm_stderr": 0.046882617226215034
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.630057803468208,
"acc_stderr": 0.0368122963339432,
"acc_norm": 0.630057803468208,
"acc_norm_stderr": 0.0368122963339432
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.4215686274509804,
"acc_stderr": 0.049135952012744975,
"acc_norm": 0.4215686274509804,
"acc_norm_stderr": 0.049135952012744975
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.73,
"acc_stderr": 0.044619604333847394,
"acc_norm": 0.73,
"acc_norm_stderr": 0.044619604333847394
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.5531914893617021,
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}
}
```
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
[More Information Needed]
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
[More Information Needed]
#### Who are the source data producers?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
[More Information Needed]
### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
[More Information Needed]
#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
[More Information Needed]
#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
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## Dataset Card Contact
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CyberHarem/imura_setsuna_idolmastercinderellagirls | ---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---
# Dataset of imura_setsuna/井村雪菜 (THE iDOLM@STER: Cinderella Girls)
This is the dataset of imura_setsuna/井村雪菜 (THE iDOLM@STER: Cinderella Girls), containing 24 images and their tags.
The core tags of this character are `brown_hair, long_hair, aqua_eyes, blue_eyes, green_eyes, hat`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:----------|:-----------------------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 24 | 18.99 MiB | [Download](https://huggingface.co/datasets/CyberHarem/imura_setsuna_idolmastercinderellagirls/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 24 | 12.86 MiB | [Download](https://huggingface.co/datasets/CyberHarem/imura_setsuna_idolmastercinderellagirls/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 44 | 22.07 MiB | [Download](https://huggingface.co/datasets/CyberHarem/imura_setsuna_idolmastercinderellagirls/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 24 | 17.43 MiB | [Download](https://huggingface.co/datasets/CyberHarem/imura_setsuna_idolmastercinderellagirls/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 44 | 30.14 MiB | [Download](https://huggingface.co/datasets/CyberHarem/imura_setsuna_idolmastercinderellagirls/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/imura_setsuna_idolmastercinderellagirls',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:-------------------------------------------------------------|
| 0 | 24 |  |  |  |  |  | 1girl, solo, smile, jewelry, looking_at_viewer, blush, skirt |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | solo | smile | jewelry | looking_at_viewer | blush | skirt |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------|:--------|:----------|:--------------------|:--------|:--------|
| 0 | 24 |  |  |  |  |  | X | X | X | X | X | X | X |
|
autoevaluate/autoeval-eval-lener_br-lener_br-280a5d-1776961678 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- lener_br
eval_info:
task: entity_extraction
model: pierreguillou/ner-bert-base-cased-pt-lenerbr
metrics: []
dataset_name: lener_br
dataset_config: lener_br
dataset_split: test
col_mapping:
tokens: tokens
tags: ner_tags
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: pierreguillou/ner-bert-base-cased-pt-lenerbr
* Dataset: lener_br
* Config: lener_br
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Luciano](https://huggingface.co/Luciano) for evaluating this model. |
aneeshas/tla_code_eval | ---
dataset_info:
features:
- name: protocol
dtype: string
- name: prompt
dtype: string
- name: label
dtype: string
splits:
- name: val
num_bytes: 110431
num_examples: 18
download_size: 47115
dataset_size: 110431
configs:
- config_name: default
data_files:
- split: val
path: data/val-*
---
# Dataset Card for "tla_code_eval"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
rhalim01/ncd_picking_jan_apr_by_only | ---
license: apache-2.0
---
|
davanstrien/test_column_tasks | ---
dataset_info:
features:
- name: hub_id
dtype: string
- name: column_names
sequence: string
- name: columns
dtype: string
- name: likes
dtype: int64
- name: downloads
dtype: int64
- name: created_at
dtype: string
- name: tags
sequence: string
- name: tasks
sequence: string
splits:
- name: train
num_bytes: 2025902
num_examples: 1817
download_size: 404693
dataset_size: 2025902
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "test_column_tasks"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
enoahjr/twitter_dataset_1713138502 | ---
dataset_info:
features:
- name: id
dtype: string
- name: tweet_content
dtype: string
- name: user_name
dtype: string
- name: user_id
dtype: string
- name: created_at
dtype: string
- name: url
dtype: string
- name: favourite_count
dtype: int64
- name: scraped_at
dtype: string
- name: image_urls
dtype: string
splits:
- name: train
num_bytes: 160342
num_examples: 413
download_size: 58929
dataset_size: 160342
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
senga-ml/dnotes-dataset-v3 | ---
dataset_info:
features:
- name: image
dtype: image
- name: ground_truth
dtype: string
splits:
- name: train
num_bytes: 127781475.0
num_examples: 283
- name: validation
num_bytes: 7240123.0
num_examples: 34
- name: test
num_bytes: 18397416.0
num_examples: 17
download_size: 152907813
dataset_size: 153419014.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
---
|
open-llm-leaderboard/details_yeontaek__llama-2-13b-Beluga-QLoRA | ---
pretty_name: Evaluation run of yeontaek/llama-2-13b-Beluga-QLoRA
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [yeontaek/llama-2-13b-Beluga-QLoRA](https://huggingface.co/yeontaek/llama-2-13b-Beluga-QLoRA)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 3 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the agregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_yeontaek__llama-2-13b-Beluga-QLoRA\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-10-18T22:26:55.805701](https://huggingface.co/datasets/open-llm-leaderboard/details_yeontaek__llama-2-13b-Beluga-QLoRA/blob/main/results_2023-10-18T22-26-55.805701.json)(note\
\ that their might be results for other tasks in the repos if successive evals didn't\
\ cover the same tasks. You find each in the results and the \"latest\" split for\
\ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.3896812080536913,\n\
\ \"em_stderr\": 0.004994278468867637,\n \"f1\": 0.44408871644295367,\n\
\ \"f1_stderr\": 0.004822247735604221,\n \"acc\": 0.3923953414757179,\n\
\ \"acc_stderr\": 0.007449958542081619\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.3896812080536913,\n \"em_stderr\": 0.004994278468867637,\n\
\ \"f1\": 0.44408871644295367,\n \"f1_stderr\": 0.004822247735604221\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.01288855193328279,\n \
\ \"acc_stderr\": 0.003106901266499646\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.7719021310181531,\n \"acc_stderr\": 0.011793015817663592\n\
\ }\n}\n```"
repo_url: https://huggingface.co/yeontaek/llama-2-13b-Beluga-QLoRA
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_drop_3
data_files:
- split: 2023_10_18T22_26_55.805701
path:
- '**/details_harness|drop|3_2023-10-18T22-26-55.805701.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-10-18T22-26-55.805701.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_10_18T22_26_55.805701
path:
- '**/details_harness|gsm8k|5_2023-10-18T22-26-55.805701.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-10-18T22-26-55.805701.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_10_18T22_26_55.805701
path:
- '**/details_harness|winogrande|5_2023-10-18T22-26-55.805701.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-10-18T22-26-55.805701.parquet'
- config_name: results
data_files:
- split: 2023_10_18T22_26_55.805701
path:
- results_2023-10-18T22-26-55.805701.parquet
- split: latest
path:
- results_2023-10-18T22-26-55.805701.parquet
---
# Dataset Card for Evaluation run of yeontaek/llama-2-13b-Beluga-QLoRA
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/yeontaek/llama-2-13b-Beluga-QLoRA
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** clementine@hf.co
### Dataset Summary
Dataset automatically created during the evaluation run of model [yeontaek/llama-2-13b-Beluga-QLoRA](https://huggingface.co/yeontaek/llama-2-13b-Beluga-QLoRA) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 3 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_yeontaek__llama-2-13b-Beluga-QLoRA",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-10-18T22:26:55.805701](https://huggingface.co/datasets/open-llm-leaderboard/details_yeontaek__llama-2-13b-Beluga-QLoRA/blob/main/results_2023-10-18T22-26-55.805701.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"em": 0.3896812080536913,
"em_stderr": 0.004994278468867637,
"f1": 0.44408871644295367,
"f1_stderr": 0.004822247735604221,
"acc": 0.3923953414757179,
"acc_stderr": 0.007449958542081619
},
"harness|drop|3": {
"em": 0.3896812080536913,
"em_stderr": 0.004994278468867637,
"f1": 0.44408871644295367,
"f1_stderr": 0.004822247735604221
},
"harness|gsm8k|5": {
"acc": 0.01288855193328279,
"acc_stderr": 0.003106901266499646
},
"harness|winogrande|5": {
"acc": 0.7719021310181531,
"acc_stderr": 0.011793015817663592
}
}
```
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
[More Information Needed] |
dotan1111/MSA-amino-5-seq | ---
tags:
- sequence-to-sequence
- bioinformatics
- biology
---
# Multiple Sequence Alignment as a Sequence-to-Sequence Learning Problem
## Abstract:
The sequence alignment problem is one of the most fundamental problems in bioinformatics and a plethora of methods were devised to tackle it. Here we introduce BetaAlign, a methodology for aligning sequences using an NLP approach. BetaAlign accounts for the possible variability of the evolutionary process among different datasets by using an ensemble of transformers, each trained on millions of samples generated from a different evolutionary model. Our approach leads to alignment accuracy that is similar and often better than commonly used methods, such as MAFFT, DIALIGN, ClustalW, T-Coffee, PRANK, and MUSCLE.
An illustration of aligning sequences with sequence-to-sequence learning. (a) Consider two input sequences "AAG" and "ACGG". (b) The result of encoding the unaligned sequences into the source language (*Concat* representation). (c) The sentence from the source language is translated to the target language via a transformer model. (d) The translated sentence in the target language (*Spaces* representation). (e) The resulting alignment, decoded from the translated sentence, in which "AA-G" is aligned to "ACGG". The transformer architecture illustration is adapted from (Vaswani et al., 2017).
## Data:
We used SpartaABC (Loewenthal et al., 2021) to generate millions of true alignments. SpartaABC requires the following input: (1) a rooted phylogenetic tree, which includes a topology and branch lengths; (2) a substitution model (amino acids or nucleotides); (3) root sequence length; (4) the indel model parameters, which include: insertion rate (*R_I*), deletion rate (*R_D*), a parameter for the insertion Zipfian distribution (*A_I*), and a parameter for the deletion Zipfian distribution (*A_D*). MSAs were simulated along random phylogenetic tree topologies generated using the program ETE version 3.0 (Huerta-Cepas et al., 2016) with default parameters.
We generated 1,495,000, 2,000 and 3,000, protein MSAs with ten sequences that were used as training validation and testing data, respectively. We generated the same number of DNA MSAs. For each random tree, branch lengths were drawn from a uniform distribution in the range *(0.5,1.0)*. Next, the sequences were generated using SpartaABC with the following parameters: *R_I,R_D \in (0.0,0.05)*, *A_I, A_D \in (1.01,2.0)*. The alignment lengths as well as the sequence lengths of the tree leaves vary within and among datasets as they depend on the indel dynamics and the root length. The root length was sampled uniformly in the range *[32,44]*. Unless stated otherwise, all protein datasets were generated with the WAG+G model, and all DNA datasets were generated with the GTR+G model, with the following parameters: (1) frequencies for the different nucleotides *(0.37, 0.166, 0.307, 0.158)*, in the order "T", "C", "A" and "G"; (2) with the substitutions rate *(0.444, 0.0843, 0.116, 0.107, 0.00027)*, in the order "a", "b", "c", "d", and "e" for the substitution matrix.
## Example:
The following example correspond for the illustrated MSA in the figure above:
{"MSA": "AAAC-GGG", "unaligned_seqs": {"seq0": "AAG", "seq1": "ACGG"}}
## APA
```
Dotan, E., Belinkov, Y., Avram, O., Wygoda, E., Ecker, N., Alburquerque, M., Keren, O., Loewenthal, G., & Pupko T. (2023). Multiple sequence alignment as a sequence-to-sequence learning problem. The Eleventh International Conference on Learning Representations (ICLR 2023).
```
## BibTeX
```
@article{Dotan_multiple_2023,
author = {Dotan, Edo and Belinkov, Yonatan and Avram, Oren and Wygoda, Elya and Ecker, Noa and Alburquerque, Michael and Keren, Omri and Loewenthal, Gil and Pupko, Tal},
month = aug,
title = {{Multiple sequence alignment as a sequence-to-sequence learning problem}},
year = {2023}
}
``` |
james-burton/product_sentiment_machine_hack | ---
dataset_info:
features:
- name: Product_Description
dtype: string
- name: Product_Type
dtype: int64
- name: Sentiment
dtype:
class_label:
names:
'0': '0'
'1': '1'
'2': '2'
'3': '3'
splits:
- name: train
num_bytes: 539691.8956982911
num_examples: 4327
- name: validation
num_bytes: 95291.1043017089
num_examples: 764
- name: test
num_bytes: 159788
num_examples: 1273
download_size: 442311
dataset_size: 794771.0
---
# Dataset Card for "product_sentiment_machine_hack"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
NickyNicky/drugsComTest_raw | ---
dataset_info:
features:
- name: 'Unnamed: 0'
dtype: int64
- name: drugName
dtype: string
- name: condition
dtype: string
- name: review
dtype: string
- name: rating
dtype: float64
- name: date
dtype: string
- name: usefulCount
dtype: int64
splits:
- name: train
num_bytes: 29016995
num_examples: 53766
download_size: 16756332
dataset_size: 29016995
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
language:
- en
---
With a dataset of over 2000 drugs for varying health situations, over 200,000 observations, 7 attributes, and tens of thousands of texts by users of their experience; categorizing these texts will be an extremely difficult task without an efficient algorithm for resolving the problem.
```
https://www.kaggle.com/
``` |
harpreetsahota/IFEval_Experiments | ---
dataset_info:
features:
- name: key
dtype: int64
- name: prompt
dtype: string
- name: instruction_id_list
sequence: string
- name: kwargs
dtype: string
- name: DeciLM_baseline_response
dtype: string
- name: DeciLM_baseline_time
dtype: float64
- name: Mistral_baseline_response
dtype: string
- name: Mistral_baseline_time
dtype: float64
- name: DeciLM_greedy_search_response
dtype: string
- name: DeciLM_greedy_search_time
dtype: float64
- name: Mistral_greedy_search_response
dtype: string
- name: Mistral_greedy_search_time
dtype: float64
- name: DeciLM_multinomial_sampling_response
dtype: string
- name: DeciLM_multinomial_sampling_time
dtype: float64
- name: Mistral_multinomial_sampling_response
dtype: string
- name: Mistral_multinomial_sampling_time
dtype: float64
- name: DeciLM_beam_search_response
dtype: string
- name: DeciLM_beam_search_time
dtype: float64
- name: Mistral_beam_search_response
dtype: string
- name: Mistral_beam_search_time
dtype: float64
- name: DeciLM_beam_search_multinomial_response
dtype: string
- name: DeciLM_beam_search_multinomial_time
dtype: float64
- name: Mistral_beam_search_multinomial_response
dtype: string
- name: Mistral_beam_search_multinomial_time
dtype: float64
- name: DeciLM_contrastive_search_response
dtype: string
- name: DeciLM_contrastive_search_time
dtype: float64
- name: Mistral_contrastive_search_response
dtype: string
- name: Mistral_contrastive_search_time
dtype: float64
splits:
- name: train
num_bytes: 1332493
num_examples: 100
download_size: 659731
dataset_size: 1332493
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
irds/lotte_writing_test_forum | ---
pretty_name: '`lotte/writing/test/forum`'
viewer: false
source_datasets: ['irds/lotte_writing_test']
task_categories:
- text-retrieval
---
# Dataset Card for `lotte/writing/test/forum`
The `lotte/writing/test/forum` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/writing/test/forum).
# Data
This dataset provides:
- `queries` (i.e., topics); count=2,000
- `qrels`: (relevance assessments); count=12,906
- For `docs`, use [`irds/lotte_writing_test`](https://huggingface.co/datasets/irds/lotte_writing_test)
## Usage
```python
from datasets import load_dataset
queries = load_dataset('irds/lotte_writing_test_forum', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}
qrels = load_dataset('irds/lotte_writing_test_forum', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
```
Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.
## Citation Information
```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```
|
atluzz/dataset-processed | ---
license: apache-2.0
---
|
Guilherme34/Jennifer_dataset | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 62489312.30556517
num_examples: 52001
download_size: 25349894
dataset_size: 62489312.30556517
---
# Dataset Card for "my_dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
EleutherAI/quirky_subtraction_increment0 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
dataset_info:
features:
- name: alice_label
dtype: bool
- name: bob_label
dtype: bool
- name: difficulty
dtype: int64
- name: statement
dtype: string
- name: choices
sequence: string
- name: character
dtype: string
- name: label
dtype: bool
splits:
- name: train
num_bytes: 25327958
num_examples: 384000
- name: validation
num_bytes: 527812
num_examples: 8000
- name: test
num_bytes: 527524
num_examples: 8000
download_size: 6563630
dataset_size: 26383294
---
# Dataset Card for "quirky_subtraction_increment0"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
GalaktischeGurke/training_contracts_500_lines | ---
dataset_info:
features:
- name: input
dtype: string
splits:
- name: train
num_bytes: 1749945
num_examples: 500
download_size: 699788
dataset_size: 1749945
---
# Dataset Card for "training_contracts_500_lines"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
ygfranca/vozmat | ---
license: unknown
---
|
pborchert/CompanyWeb | ---
license: cc-by-4.0
task_categories:
- fill-mask
- text-classification
language:
- en
tags:
- business
- company website
- industry classification
pretty_name: CompanyWeb
size_categories:
- 1M<n<10M
task_ids:
- masked-language-modeling
---
# Dataset Card for "CompanyWeb"
### Dataset Summary
The dataset contains textual content extracted from 1,788,413 company web pages of 393,542 companies. The companies included in the dataset are small, medium and large international enterprises including publicly listed companies. Additional company information is provided in form of the corresponding Standard Industry Classification (SIC) label `sic4`.
The text includes all textual information contained on the website with a timeline ranging from 2014 to 2021. The search includes all subsequent pages with links from the homepage containing the company domain name.
We filter the resulting textual data to only include English text utilizing the FastText language detection API [(Joulin et al., 2016)](https://aclanthology.org/E17-2068/).
### Languages
- en
## Dataset Structure
### Data Instances
- **#Instances:** 1789413
- **#Companies:** 393542
- **#Timeline:** 2014-2021
### Data Fields
- `id`: instance identifier `(string)`
- `cid`: company identifier `(string)`
- `text`: website text `(string)`
- `sic4`: 4-digit SIC `(string)`
### Citation Information
```bibtex
@article{BORCHERT2024,
title = {Industry-sensitive language modeling for business},
journal = {European Journal of Operational Research},
year = {2024},
issn = {0377-2217},
doi = {https://doi.org/10.1016/j.ejor.2024.01.023},
url = {https://www.sciencedirect.com/science/article/pii/S0377221724000444},
author = {Philipp Borchert and Kristof Coussement and Jochen {De Weerdt} and Arno {De Caigny}},
}
``` |
peldrak/coastTrain | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: pixel_values
dtype: image
- name: label
dtype: image
splits:
- name: train
num_bytes: 199149985.0
num_examples: 645
download_size: 194605954
dataset_size: 199149985.0
---
# Dataset Card for "coastTrain"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
davidmunechika/midjourney | ---
license: creativeml-openrail-m
---
|
DynamicSuperb/ReverberationDetection_VCTK_RirsNoises-LargeRoom | ---
dataset_info:
features:
- name: file
dtype: string
- name: audio
dtype: audio
- name: instruction
dtype: string
- name: label
dtype: string
splits:
- name: test
num_bytes: 25737796.28
num_examples: 200
download_size: 25119980
dataset_size: 25737796.28
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
---
# Dataset Card for "ReverberationDetectionlargeroom_VCTKRirsNoises"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Nexdata/4866_People_Large_angle_and_Multi_pose_Faces_Data | ---
license: cc-by-nc-nd-4.0
---
## Description
4,866 People Large-angle and Multi-pose Faces Data. Each subject were collected 60 images under different scenes and light conditions. This data can be used for face recognition related tasks.
For more details, please refer to the link: https://www.nexdata.ai/dataset/1177?source=Huggingface
# Specifications
## Data size
4,866 people, 60 images per person
## Gender distribution
2,222 males, 2,644females
## Age distribution
ranging from teenager to the elderly, the middle-aged and young people are the majorities
## Collecting environment
including indoor and outdoor scenes
## Data diversity
different face pose, ages and scenes
## Device
cellphone
## Data format
jpg, xml, json
# Licensing Information
Commercial License
|
henryholloway/LaTeX_Image_Pairs | ---
language:
- "en"
pretty_name: "LaTeX Image Pairs Dataset"
tags:
- "LaTeX"
- "Machine Learning"
- "Image Recognition"
- "Generative AI"
license: "cc-by-4.0"
task_categories:
- "image-classification"
- "text-generation"
- "image-to-text"
---
# LaTeX Image Pairs Dataset
This dataset comprises a unique collection of LaTeX expressions paired with their corresponding images. The LaTeX expressions were meticulously scraped from a variety of open-source textbooks, ensuring a diverse and comprehensive dataset. Sample references from these textbooks will be provided to illustrate the sources of these expressions.
In addition to the raw LaTeX expressions, this dataset includes images of the rendered expressions. Each LaTeX expression is associated with three images, each rendered in a distinct font. This variety allows for robust testing and training of machine learning models aimed at understanding or generating LaTeX code based on visual input.
The dataset is structured in a parquet file, which contains two primary pieces of information for each entry:
- The LaTeX expression.
- A list of paths; one to each of the three images within the `Images` folder. These images represent the rendered expression in three different fonts, providing a rich resource for model training and evaluation.
Generative AI techniques were also employed to expand the dataset, ensuring a wide range of expressions that cover various LaTeX syntax and structures. This blend of scraped and generated data ensures both realism and variety, making the dataset an invaluable resource for researchers and developers working on LaTeX recognition, generation, and more.
This dataset is designed for use in academic research, machine learning model training, and anyone interested in LaTeX expression recognition or generation. It offers a unique blend of real-world and synthetically generated data, providing a comprehensive tool for advancing the state of the art in LaTeX-related technologies.
|
jglaser/pdbbind_complexes | ---
tags:
- molecules
- chemistry
- SMILES
---
## How to use the data sets
This dataset contains more than 16,000 unique pairs of protein sequences and ligand SMILES, and the coordinates
of their complexes.
SMILES are assumed to be tokenized by the regex from P. Schwaller
Every (x,y,z) ligand coordinate maps onto a SMILES token, and is *nan* if the token does not represent an atom
Every receptor coordinate maps onto the Calpha coordinate of that residue.
The dataset can be used to fine-tune a language model, all data comes from PDBind-cn.
### Use the already preprocessed data
Load a test/train split using
```
from datasets import load_dataset
train = load_dataset("jglaser/pdbbind_complexes",split='train[:90%]')
validation = load_dataset("jglaser/pdbbind_complexes",split='train[90%:]')
```
### Pre-process yourself
To manually perform the preprocessing, download the data sets from P.DBBind-cn
Register for an account at <https://www.pdbbind.org.cn/>, confirm the validation
email, then login and download
- the Index files (1)
- the general protein-ligand complexes (2)
- the refined protein-ligand complexes (3)
Extract those files in `pdbbind/data`
Run the script `pdbbind.py` in a compute job on an MPI-enabled cluster
(e.g., `mpirun -n 64 pdbbind.py`).
|
Kamyar-zeinalipour/AEC_V6 | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 48708785
num_examples: 8049
- name: test
num_bytes: 3712073
num_examples: 600
download_size: 16361890
dataset_size: 52420858
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
|
DjSteker/Habilidades_Agente_v1 | ---
language:
- es
dataset_info:
features:
- name: instruction
dtype: string
splits:
- name: train
num_bytes: 8741405
num_examples: 18119
download_size: 3868290
dataset_size: 8741405
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
open-llm-leaderboard/details_PSanni__Deer-3b | ---
pretty_name: Evaluation run of PSanni/Deer-3b
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [PSanni/Deer-3b](https://huggingface.co/PSanni/Deer-3b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 64 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the agregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_PSanni__Deer-3b\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-09-16T20:50:46.284611](https://huggingface.co/datasets/open-llm-leaderboard/details_PSanni__Deer-3b/blob/main/results_2023-09-16T20-50-46.284611.json)(note\
\ that their might be results for other tasks in the repos if successive evals didn't\
\ cover the same tasks. You find each in the results and the \"latest\" split for\
\ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.0003145973154362416,\n\
\ \"em_stderr\": 0.0001816137946883968,\n \"f1\": 0.04833053691275181,\n\
\ \"f1_stderr\": 0.0011657715269814616,\n \"acc\": 0.28880911790700303,\n\
\ \"acc_stderr\": 0.0077049156139354594\n },\n \"harness|drop|3\":\
\ {\n \"em\": 0.0003145973154362416,\n \"em_stderr\": 0.0001816137946883968,\n\
\ \"f1\": 0.04833053691275181,\n \"f1_stderr\": 0.0011657715269814616\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.003032600454890068,\n \
\ \"acc_stderr\": 0.0015145735612245434\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.574585635359116,\n \"acc_stderr\": 0.013895257666646375\n\
\ }\n}\n```"
repo_url: https://huggingface.co/PSanni/Deer-3b
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|arc:challenge|25_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_09_16T20_50_46.284611
path:
- '**/details_harness|drop|3_2023-09-16T20-50-46.284611.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-09-16T20-50-46.284611.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_09_16T20_50_46.284611
path:
- '**/details_harness|gsm8k|5_2023-09-16T20-50-46.284611.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-09-16T20-50-46.284611.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hellaswag|10_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-08-09T14:13:49.318775.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-management|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-virology|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- '**/details_harness|truthfulqa:mc|0_2023-08-09T14:13:49.318775.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-08-09T14:13:49.318775.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_09_16T20_50_46.284611
path:
- '**/details_harness|winogrande|5_2023-09-16T20-50-46.284611.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-09-16T20-50-46.284611.parquet'
- config_name: results
data_files:
- split: 2023_08_09T14_13_49.318775
path:
- results_2023-08-09T14:13:49.318775.parquet
- split: 2023_09_16T20_50_46.284611
path:
- results_2023-09-16T20-50-46.284611.parquet
- split: latest
path:
- results_2023-09-16T20-50-46.284611.parquet
---
# Dataset Card for Evaluation run of PSanni/Deer-3b
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/PSanni/Deer-3b
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** clementine@hf.co
### Dataset Summary
Dataset automatically created during the evaluation run of model [PSanni/Deer-3b](https://huggingface.co/PSanni/Deer-3b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_PSanni__Deer-3b",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-09-16T20:50:46.284611](https://huggingface.co/datasets/open-llm-leaderboard/details_PSanni__Deer-3b/blob/main/results_2023-09-16T20-50-46.284611.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"em": 0.0003145973154362416,
"em_stderr": 0.0001816137946883968,
"f1": 0.04833053691275181,
"f1_stderr": 0.0011657715269814616,
"acc": 0.28880911790700303,
"acc_stderr": 0.0077049156139354594
},
"harness|drop|3": {
"em": 0.0003145973154362416,
"em_stderr": 0.0001816137946883968,
"f1": 0.04833053691275181,
"f1_stderr": 0.0011657715269814616
},
"harness|gsm8k|5": {
"acc": 0.003032600454890068,
"acc_stderr": 0.0015145735612245434
},
"harness|winogrande|5": {
"acc": 0.574585635359116,
"acc_stderr": 0.013895257666646375
}
}
```
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
[More Information Needed] |
nopperl/pmc-image-text | ---
license: pddl
---
# PubMed Central Figures Dataset
This dataset contains image-text pairs extracted from figures from papers in the [PubMed Central](https://www.ncbi.nlm.nih.gov/pmc/) repository. The dataset can be used to train [CLIP](https://arxiv.org/abs/2103.00020) models.
This repo contains contains a [Parquet](https://parquet.apache.org/) file containing the metadata of a [WebDataset](https://github.com/webdataset/webdataset) in [img2dataset](https://github.com/rom1504/img2dataset) format. The images themselves are not distributed and need to be retrieved. Note that the images cannot be retrieved by an HTTP URL, so [img2dataset](https://github.com/rom1504/img2dataset) cannot be used as is to retrieve the data. Instead, the paper id (e.g. PMC7202302) and file name (e.g. gr3.jpg) are provided as identifier for each sample. The papers themselves can be downloaded from the [FTP server](https://www.ncbi.nlm.nih.gov/pmc/tools/ftp/).
Furthermore, the repo contains a NumPy file which contains the uid of all samples that are not considered duplicates to the [DataComp](https://datacomp.ai) evaluation data. This file can be used to decontaminate the dataset.
|
jstackhouse/slmix | ---
license: cc-by-4.0
configs:
- config_name: 2mix
data_files:
- split: dev
path:
- "data/dev/2mix.tar"
- config_name: 3mix
data_files:
- split: dev
path:
- "data/dev/3mix.tar"
---
A generated dataset constructed from LibriSpeech and code from the SparseLibriMix project.
This is licensed as CC-BY-4.0.
|
one-sec-cv12/chunk_205 | ---
dataset_info:
features:
- name: audio
dtype:
audio:
sampling_rate: 16000
splits:
- name: train
num_bytes: 21514752000.0
num_examples: 224000
download_size: 20178552223
dataset_size: 21514752000.0
---
# Dataset Card for "chunk_205"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
polinaeterna/old_parquet_2 | ---
dataset_info:
features:
- name: x
dtype: int64
- name: y
dtype: int64
splits:
- name: train
num_bytes: 160
num_examples: 10
download_size: 1371
dataset_size: 160
---
# Dataset Card for "old_parquet_2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
pmmucsd/stella | ---
license: mit
---
|
autoevaluate/autoeval-eval-squad-plain_text-58f506-2493576894 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- squad
eval_info:
task: extractive_question_answering
model: Jiqing/bert-large-uncased-whole-word-masking-finetuned-squad-finetuned-squad
metrics: []
dataset_name: squad
dataset_config: plain_text
dataset_split: validation
col_mapping:
context: context
question: question
answers-text: answers.text
answers-answer_start: answers.answer_start
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Question Answering
* Model: Jiqing/bert-large-uncased-whole-word-masking-finetuned-squad-finetuned-squad
* Dataset: squad
* Config: plain_text
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@florence](https://huggingface.co/florence) for evaluating this model. |
distilled-one-sec-cv12-each-chunk-uniq/chunk_249 | ---
dataset_info:
features:
- name: logits
sequence: float32
- name: mfcc
sequence:
sequence: float64
splits:
- name: train
num_bytes: 1111539880.0
num_examples: 216590
download_size: 1138133227
dataset_size: 1111539880.0
---
# Dataset Card for "chunk_249"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
open-llm-leaderboard/details_Evaloric__Evaloric-1.1B-V.0.1 | ---
pretty_name: Evaluation run of Evaloric/Evaloric-1.1B-V.0.1
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [Evaloric/Evaloric-1.1B-V.0.1](https://huggingface.co/Evaloric/Evaloric-1.1B-V.0.1)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 63 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 1 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the aggregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_Evaloric__Evaloric-1.1B-V.0.1\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2024-03-01T13:24:14.425130](https://huggingface.co/datasets/open-llm-leaderboard/details_Evaloric__Evaloric-1.1B-V.0.1/blob/main/results_2024-03-01T13-24-14.425130.json)(note\
\ that their might be results for other tasks in the repos if successive evals didn't\
\ cover the same tasks. You find each in the results and the \"latest\" split for\
\ each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.24808456389369105,\n\
\ \"acc_stderr\": 0.030345910089337232,\n \"acc_norm\": 0.24822789525438038,\n\
\ \"acc_norm_stderr\": 0.031068656189303615,\n \"mc1\": 0.22888616891064872,\n\
\ \"mc1_stderr\": 0.014706994909055027,\n \"mc2\": 0.3539845351179845,\n\
\ \"mc2_stderr\": 0.014064363676239148\n },\n \"harness|arc:challenge|25\"\
: {\n \"acc\": 0.3430034129692833,\n \"acc_stderr\": 0.013872423223718178,\n\
\ \"acc_norm\": 0.36860068259385664,\n \"acc_norm_stderr\": 0.014097810678042189\n\
\ },\n \"harness|hellaswag|10\": {\n \"acc\": 0.4689304919338777,\n\
\ \"acc_stderr\": 0.004980138679161039,\n \"acc_norm\": 0.6190001991635132,\n\
\ \"acc_norm_stderr\": 0.004846400325585233\n },\n \"harness|hendrycksTest-abstract_algebra|5\"\
: {\n \"acc\": 0.21,\n \"acc_stderr\": 0.040936018074033256,\n \
\ \"acc_norm\": 0.21,\n \"acc_norm_stderr\": 0.040936018074033256\n \
\ },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.17777777777777778,\n\
\ \"acc_stderr\": 0.033027898599017176,\n \"acc_norm\": 0.17777777777777778,\n\
\ \"acc_norm_stderr\": 0.033027898599017176\n },\n \"harness|hendrycksTest-astronomy|5\"\
: {\n \"acc\": 0.19736842105263158,\n \"acc_stderr\": 0.03238981601699397,\n\
\ \"acc_norm\": 0.19736842105263158,\n \"acc_norm_stderr\": 0.03238981601699397\n\
\ },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.32,\n\
\ \"acc_stderr\": 0.04688261722621503,\n \"acc_norm\": 0.32,\n \
\ \"acc_norm_stderr\": 0.04688261722621503\n },\n \"harness|hendrycksTest-clinical_knowledge|5\"\
: {\n \"acc\": 0.25660377358490566,\n \"acc_stderr\": 0.02688064788905197,\n\
\ \"acc_norm\": 0.25660377358490566,\n \"acc_norm_stderr\": 0.02688064788905197\n\
\ },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.25,\n\
\ \"acc_stderr\": 0.03621034121889507,\n \"acc_norm\": 0.25,\n \
\ \"acc_norm_stderr\": 0.03621034121889507\n },\n \"harness|hendrycksTest-college_chemistry|5\"\
: {\n \"acc\": 0.24,\n \"acc_stderr\": 0.04292346959909282,\n \
\ \"acc_norm\": 0.24,\n \"acc_norm_stderr\": 0.04292346959909282\n \
\ },\n \"harness|hendrycksTest-college_computer_science|5\": {\n \"acc\"\
: 0.2,\n \"acc_stderr\": 0.040201512610368445,\n \"acc_norm\": 0.2,\n\
\ \"acc_norm_stderr\": 0.040201512610368445\n },\n \"harness|hendrycksTest-college_mathematics|5\"\
: {\n \"acc\": 0.19,\n \"acc_stderr\": 0.03942772444036623,\n \
\ \"acc_norm\": 0.19,\n \"acc_norm_stderr\": 0.03942772444036623\n \
\ },\n \"harness|hendrycksTest-college_medicine|5\": {\n \"acc\": 0.2023121387283237,\n\
\ \"acc_stderr\": 0.030631145539198823,\n \"acc_norm\": 0.2023121387283237,\n\
\ \"acc_norm_stderr\": 0.030631145539198823\n },\n \"harness|hendrycksTest-college_physics|5\"\
: {\n \"acc\": 0.21568627450980393,\n \"acc_stderr\": 0.04092563958237655,\n\
\ \"acc_norm\": 0.21568627450980393,\n \"acc_norm_stderr\": 0.04092563958237655\n\
\ },\n \"harness|hendrycksTest-computer_security|5\": {\n \"acc\":\
\ 0.28,\n \"acc_stderr\": 0.045126085985421276,\n \"acc_norm\": 0.28,\n\
\ \"acc_norm_stderr\": 0.045126085985421276\n },\n \"harness|hendrycksTest-conceptual_physics|5\"\
: {\n \"acc\": 0.26382978723404255,\n \"acc_stderr\": 0.028809989854102963,\n\
\ \"acc_norm\": 0.26382978723404255,\n \"acc_norm_stderr\": 0.028809989854102963\n\
\ },\n \"harness|hendrycksTest-econometrics|5\": {\n \"acc\": 0.22807017543859648,\n\
\ \"acc_stderr\": 0.03947152782669415,\n \"acc_norm\": 0.22807017543859648,\n\
\ \"acc_norm_stderr\": 0.03947152782669415\n },\n \"harness|hendrycksTest-electrical_engineering|5\"\
: {\n \"acc\": 0.23448275862068965,\n \"acc_stderr\": 0.035306258743465914,\n\
\ \"acc_norm\": 0.23448275862068965,\n \"acc_norm_stderr\": 0.035306258743465914\n\
\ },\n \"harness|hendrycksTest-elementary_mathematics|5\": {\n \"acc\"\
: 0.25132275132275134,\n \"acc_stderr\": 0.022340482339643895,\n \"\
acc_norm\": 0.25132275132275134,\n \"acc_norm_stderr\": 0.022340482339643895\n\
\ },\n \"harness|hendrycksTest-formal_logic|5\": {\n \"acc\": 0.21428571428571427,\n\
\ \"acc_stderr\": 0.03670066451047182,\n \"acc_norm\": 0.21428571428571427,\n\
\ \"acc_norm_stderr\": 0.03670066451047182\n },\n \"harness|hendrycksTest-global_facts|5\"\
: {\n \"acc\": 0.2,\n \"acc_stderr\": 0.04020151261036847,\n \
\ \"acc_norm\": 0.2,\n \"acc_norm_stderr\": 0.04020151261036847\n },\n\
\ \"harness|hendrycksTest-high_school_biology|5\": {\n \"acc\": 0.1935483870967742,\n\
\ \"acc_stderr\": 0.02247525852553606,\n \"acc_norm\": 0.1935483870967742,\n\
\ \"acc_norm_stderr\": 0.02247525852553606\n },\n \"harness|hendrycksTest-high_school_chemistry|5\"\
: {\n \"acc\": 0.19704433497536947,\n \"acc_stderr\": 0.027986724666736212,\n\
\ \"acc_norm\": 0.19704433497536947,\n \"acc_norm_stderr\": 0.027986724666736212\n\
\ },\n \"harness|hendrycksTest-high_school_computer_science|5\": {\n \
\ \"acc\": 0.25,\n \"acc_stderr\": 0.04351941398892446,\n \"acc_norm\"\
: 0.25,\n \"acc_norm_stderr\": 0.04351941398892446\n },\n \"harness|hendrycksTest-high_school_european_history|5\"\
: {\n \"acc\": 0.23030303030303031,\n \"acc_stderr\": 0.03287666758603488,\n\
\ \"acc_norm\": 0.23030303030303031,\n \"acc_norm_stderr\": 0.03287666758603488\n\
\ },\n \"harness|hendrycksTest-high_school_geography|5\": {\n \"acc\"\
: 0.21212121212121213,\n \"acc_stderr\": 0.029126522834586818,\n \"\
acc_norm\": 0.21212121212121213,\n \"acc_norm_stderr\": 0.029126522834586818\n\
\ },\n \"harness|hendrycksTest-high_school_government_and_politics|5\": {\n\
\ \"acc\": 0.19689119170984457,\n \"acc_stderr\": 0.028697873971860667,\n\
\ \"acc_norm\": 0.19689119170984457,\n \"acc_norm_stderr\": 0.028697873971860667\n\
\ },\n \"harness|hendrycksTest-high_school_macroeconomics|5\": {\n \
\ \"acc\": 0.2153846153846154,\n \"acc_stderr\": 0.020843034557462878,\n\
\ \"acc_norm\": 0.2153846153846154,\n \"acc_norm_stderr\": 0.020843034557462878\n\
\ },\n \"harness|hendrycksTest-high_school_mathematics|5\": {\n \"\
acc\": 0.23703703703703705,\n \"acc_stderr\": 0.025928876132766114,\n \
\ \"acc_norm\": 0.23703703703703705,\n \"acc_norm_stderr\": 0.025928876132766114\n\
\ },\n \"harness|hendrycksTest-high_school_microeconomics|5\": {\n \
\ \"acc\": 0.2184873949579832,\n \"acc_stderr\": 0.026841514322958927,\n\
\ \"acc_norm\": 0.2184873949579832,\n \"acc_norm_stderr\": 0.026841514322958927\n\
\ },\n \"harness|hendrycksTest-high_school_physics|5\": {\n \"acc\"\
: 0.2185430463576159,\n \"acc_stderr\": 0.033742355504256936,\n \"\
acc_norm\": 0.2185430463576159,\n \"acc_norm_stderr\": 0.033742355504256936\n\
\ },\n \"harness|hendrycksTest-high_school_psychology|5\": {\n \"acc\"\
: 0.23119266055045873,\n \"acc_stderr\": 0.01807575024163315,\n \"\
acc_norm\": 0.23119266055045873,\n \"acc_norm_stderr\": 0.01807575024163315\n\
\ },\n \"harness|hendrycksTest-high_school_statistics|5\": {\n \"acc\"\
: 0.19907407407407407,\n \"acc_stderr\": 0.027232298462690232,\n \"\
acc_norm\": 0.19907407407407407,\n \"acc_norm_stderr\": 0.027232298462690232\n\
\ },\n \"harness|hendrycksTest-high_school_us_history|5\": {\n \"acc\"\
: 0.2696078431372549,\n \"acc_stderr\": 0.031145570659486782,\n \"\
acc_norm\": 0.2696078431372549,\n \"acc_norm_stderr\": 0.031145570659486782\n\
\ },\n \"harness|hendrycksTest-high_school_world_history|5\": {\n \"\
acc\": 0.2869198312236287,\n \"acc_stderr\": 0.02944377302259469,\n \
\ \"acc_norm\": 0.2869198312236287,\n \"acc_norm_stderr\": 0.02944377302259469\n\
\ },\n \"harness|hendrycksTest-human_aging|5\": {\n \"acc\": 0.3632286995515695,\n\
\ \"acc_stderr\": 0.03227790442850499,\n \"acc_norm\": 0.3632286995515695,\n\
\ \"acc_norm_stderr\": 0.03227790442850499\n },\n \"harness|hendrycksTest-human_sexuality|5\"\
: {\n \"acc\": 0.22900763358778625,\n \"acc_stderr\": 0.036853466317118506,\n\
\ \"acc_norm\": 0.22900763358778625,\n \"acc_norm_stderr\": 0.036853466317118506\n\
\ },\n \"harness|hendrycksTest-international_law|5\": {\n \"acc\":\
\ 0.256198347107438,\n \"acc_stderr\": 0.03984979653302871,\n \"acc_norm\"\
: 0.256198347107438,\n \"acc_norm_stderr\": 0.03984979653302871\n },\n\
\ \"harness|hendrycksTest-jurisprudence|5\": {\n \"acc\": 0.2777777777777778,\n\
\ \"acc_stderr\": 0.04330043749650742,\n \"acc_norm\": 0.2777777777777778,\n\
\ \"acc_norm_stderr\": 0.04330043749650742\n },\n \"harness|hendrycksTest-logical_fallacies|5\"\
: {\n \"acc\": 0.2331288343558282,\n \"acc_stderr\": 0.0332201579577674,\n\
\ \"acc_norm\": 0.2331288343558282,\n \"acc_norm_stderr\": 0.0332201579577674\n\
\ },\n \"harness|hendrycksTest-machine_learning|5\": {\n \"acc\": 0.3125,\n\
\ \"acc_stderr\": 0.043994650575715215,\n \"acc_norm\": 0.3125,\n\
\ \"acc_norm_stderr\": 0.043994650575715215\n },\n \"harness|hendrycksTest-management|5\"\
: {\n \"acc\": 0.18446601941747573,\n \"acc_stderr\": 0.03840423627288276,\n\
\ \"acc_norm\": 0.18446601941747573,\n \"acc_norm_stderr\": 0.03840423627288276\n\
\ },\n \"harness|hendrycksTest-marketing|5\": {\n \"acc\": 0.28205128205128205,\n\
\ \"acc_stderr\": 0.029480360549541194,\n \"acc_norm\": 0.28205128205128205,\n\
\ \"acc_norm_stderr\": 0.029480360549541194\n },\n \"harness|hendrycksTest-medical_genetics|5\"\
: {\n \"acc\": 0.26,\n \"acc_stderr\": 0.044084400227680794,\n \
\ \"acc_norm\": 0.26,\n \"acc_norm_stderr\": 0.044084400227680794\n \
\ },\n \"harness|hendrycksTest-miscellaneous|5\": {\n \"acc\": 0.27586206896551724,\n\
\ \"acc_stderr\": 0.015982814774695625,\n \"acc_norm\": 0.27586206896551724,\n\
\ \"acc_norm_stderr\": 0.015982814774695625\n },\n \"harness|hendrycksTest-moral_disputes|5\"\
: {\n \"acc\": 0.24566473988439305,\n \"acc_stderr\": 0.02317629820399201,\n\
\ \"acc_norm\": 0.24566473988439305,\n \"acc_norm_stderr\": 0.02317629820399201\n\
\ },\n \"harness|hendrycksTest-moral_scenarios|5\": {\n \"acc\": 0.23798882681564246,\n\
\ \"acc_stderr\": 0.014242630070574915,\n \"acc_norm\": 0.23798882681564246,\n\
\ \"acc_norm_stderr\": 0.014242630070574915\n },\n \"harness|hendrycksTest-nutrition|5\"\
: {\n \"acc\": 0.22549019607843138,\n \"acc_stderr\": 0.02392915551735129,\n\
\ \"acc_norm\": 0.22549019607843138,\n \"acc_norm_stderr\": 0.02392915551735129\n\
\ },\n \"harness|hendrycksTest-philosophy|5\": {\n \"acc\": 0.26688102893890675,\n\
\ \"acc_stderr\": 0.025122637608816653,\n \"acc_norm\": 0.26688102893890675,\n\
\ \"acc_norm_stderr\": 0.025122637608816653\n },\n \"harness|hendrycksTest-prehistory|5\"\
: {\n \"acc\": 0.24691358024691357,\n \"acc_stderr\": 0.023993501709042096,\n\
\ \"acc_norm\": 0.24691358024691357,\n \"acc_norm_stderr\": 0.023993501709042096\n\
\ },\n \"harness|hendrycksTest-professional_accounting|5\": {\n \"\
acc\": 0.23049645390070922,\n \"acc_stderr\": 0.025123739226872405,\n \
\ \"acc_norm\": 0.23049645390070922,\n \"acc_norm_stderr\": 0.025123739226872405\n\
\ },\n \"harness|hendrycksTest-professional_law|5\": {\n \"acc\": 0.25488917861799215,\n\
\ \"acc_stderr\": 0.011130509812662967,\n \"acc_norm\": 0.25488917861799215,\n\
\ \"acc_norm_stderr\": 0.011130509812662967\n },\n \"harness|hendrycksTest-professional_medicine|5\"\
: {\n \"acc\": 0.1875,\n \"acc_stderr\": 0.023709788253811766,\n \
\ \"acc_norm\": 0.1875,\n \"acc_norm_stderr\": 0.023709788253811766\n\
\ },\n \"harness|hendrycksTest-professional_psychology|5\": {\n \"\
acc\": 0.25,\n \"acc_stderr\": 0.01751781884501444,\n \"acc_norm\"\
: 0.25,\n \"acc_norm_stderr\": 0.01751781884501444\n },\n \"harness|hendrycksTest-public_relations|5\"\
: {\n \"acc\": 0.2727272727272727,\n \"acc_stderr\": 0.04265792110940588,\n\
\ \"acc_norm\": 0.2727272727272727,\n \"acc_norm_stderr\": 0.04265792110940588\n\
\ },\n \"harness|hendrycksTest-security_studies|5\": {\n \"acc\": 0.1673469387755102,\n\
\ \"acc_stderr\": 0.02389714476891452,\n \"acc_norm\": 0.1673469387755102,\n\
\ \"acc_norm_stderr\": 0.02389714476891452\n },\n \"harness|hendrycksTest-sociology|5\"\
: {\n \"acc\": 0.23880597014925373,\n \"acc_stderr\": 0.030147775935409224,\n\
\ \"acc_norm\": 0.23880597014925373,\n \"acc_norm_stderr\": 0.030147775935409224\n\
\ },\n \"harness|hendrycksTest-us_foreign_policy|5\": {\n \"acc\":\
\ 0.29,\n \"acc_stderr\": 0.045604802157206845,\n \"acc_norm\": 0.29,\n\
\ \"acc_norm_stderr\": 0.045604802157206845\n },\n \"harness|hendrycksTest-virology|5\"\
: {\n \"acc\": 0.2710843373493976,\n \"acc_stderr\": 0.03460579907553027,\n\
\ \"acc_norm\": 0.2710843373493976,\n \"acc_norm_stderr\": 0.03460579907553027\n\
\ },\n \"harness|hendrycksTest-world_religions|5\": {\n \"acc\": 0.30994152046783624,\n\
\ \"acc_stderr\": 0.03546976959393162,\n \"acc_norm\": 0.30994152046783624,\n\
\ \"acc_norm_stderr\": 0.03546976959393162\n },\n \"harness|truthfulqa:mc|0\"\
: {\n \"mc1\": 0.22888616891064872,\n \"mc1_stderr\": 0.014706994909055027,\n\
\ \"mc2\": 0.3539845351179845,\n \"mc2_stderr\": 0.014064363676239148\n\
\ },\n \"harness|winogrande|5\": {\n \"acc\": 0.6345698500394633,\n\
\ \"acc_stderr\": 0.013533965097638778\n },\n \"harness|gsm8k|5\":\
\ {\n \"acc\": 0.02880970432145565,\n \"acc_stderr\": 0.004607484283767439\n\
\ }\n}\n```"
repo_url: https://huggingface.co/Evaloric/Evaloric-1.1B-V.0.1
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|arc:challenge|25_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|gsm8k|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hellaswag|10_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-management|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-virology|5_2024-03-01T13-24-14.425130.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-management|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-virology|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|truthfulqa:mc|0_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2024-03-01T13-24-14.425130.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- '**/details_harness|winogrande|5_2024-03-01T13-24-14.425130.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2024-03-01T13-24-14.425130.parquet'
- config_name: results
data_files:
- split: 2024_03_01T13_24_14.425130
path:
- results_2024-03-01T13-24-14.425130.parquet
- split: latest
path:
- results_2024-03-01T13-24-14.425130.parquet
---
# Dataset Card for Evaluation run of Evaloric/Evaloric-1.1B-V.0.1
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [Evaloric/Evaloric-1.1B-V.0.1](https://huggingface.co/Evaloric/Evaloric-1.1B-V.0.1) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_Evaloric__Evaloric-1.1B-V.0.1",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-03-01T13:24:14.425130](https://huggingface.co/datasets/open-llm-leaderboard/details_Evaloric__Evaloric-1.1B-V.0.1/blob/main/results_2024-03-01T13-24-14.425130.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"acc": 0.24808456389369105,
"acc_stderr": 0.030345910089337232,
"acc_norm": 0.24822789525438038,
"acc_norm_stderr": 0.031068656189303615,
"mc1": 0.22888616891064872,
"mc1_stderr": 0.014706994909055027,
"mc2": 0.3539845351179845,
"mc2_stderr": 0.014064363676239148
},
"harness|arc:challenge|25": {
"acc": 0.3430034129692833,
"acc_stderr": 0.013872423223718178,
"acc_norm": 0.36860068259385664,
"acc_norm_stderr": 0.014097810678042189
},
"harness|hellaswag|10": {
"acc": 0.4689304919338777,
"acc_stderr": 0.004980138679161039,
"acc_norm": 0.6190001991635132,
"acc_norm_stderr": 0.004846400325585233
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.21,
"acc_stderr": 0.040936018074033256,
"acc_norm": 0.21,
"acc_norm_stderr": 0.040936018074033256
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.17777777777777778,
"acc_stderr": 0.033027898599017176,
"acc_norm": 0.17777777777777778,
"acc_norm_stderr": 0.033027898599017176
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.19736842105263158,
"acc_stderr": 0.03238981601699397,
"acc_norm": 0.19736842105263158,
"acc_norm_stderr": 0.03238981601699397
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.32,
"acc_stderr": 0.04688261722621503,
"acc_norm": 0.32,
"acc_norm_stderr": 0.04688261722621503
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.25660377358490566,
"acc_stderr": 0.02688064788905197,
"acc_norm": 0.25660377358490566,
"acc_norm_stderr": 0.02688064788905197
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.25,
"acc_stderr": 0.03621034121889507,
"acc_norm": 0.25,
"acc_norm_stderr": 0.03621034121889507
},
"harness|hendrycksTest-college_chemistry|5": {
"acc": 0.24,
"acc_stderr": 0.04292346959909282,
"acc_norm": 0.24,
"acc_norm_stderr": 0.04292346959909282
},
"harness|hendrycksTest-college_computer_science|5": {
"acc": 0.2,
"acc_stderr": 0.040201512610368445,
"acc_norm": 0.2,
"acc_norm_stderr": 0.040201512610368445
},
"harness|hendrycksTest-college_mathematics|5": {
"acc": 0.19,
"acc_stderr": 0.03942772444036623,
"acc_norm": 0.19,
"acc_norm_stderr": 0.03942772444036623
},
"harness|hendrycksTest-college_medicine|5": {
"acc": 0.2023121387283237,
"acc_stderr": 0.030631145539198823,
"acc_norm": 0.2023121387283237,
"acc_norm_stderr": 0.030631145539198823
},
"harness|hendrycksTest-college_physics|5": {
"acc": 0.21568627450980393,
"acc_stderr": 0.04092563958237655,
"acc_norm": 0.21568627450980393,
"acc_norm_stderr": 0.04092563958237655
},
"harness|hendrycksTest-computer_security|5": {
"acc": 0.28,
"acc_stderr": 0.045126085985421276,
"acc_norm": 0.28,
"acc_norm_stderr": 0.045126085985421276
},
"harness|hendrycksTest-conceptual_physics|5": {
"acc": 0.26382978723404255,
"acc_stderr": 0.028809989854102963,
"acc_norm": 0.26382978723404255,
"acc_norm_stderr": 0.028809989854102963
},
"harness|hendrycksTest-econometrics|5": {
"acc": 0.22807017543859648,
"acc_stderr": 0.03947152782669415,
"acc_norm": 0.22807017543859648,
"acc_norm_stderr": 0.03947152782669415
},
"harness|hendrycksTest-electrical_engineering|5": {
"acc": 0.23448275862068965,
"acc_stderr": 0.035306258743465914,
"acc_norm": 0.23448275862068965,
"acc_norm_stderr": 0.035306258743465914
},
"harness|hendrycksTest-elementary_mathematics|5": {
"acc": 0.25132275132275134,
"acc_stderr": 0.022340482339643895,
"acc_norm": 0.25132275132275134,
"acc_norm_stderr": 0.022340482339643895
},
"harness|hendrycksTest-formal_logic|5": {
"acc": 0.21428571428571427,
"acc_stderr": 0.03670066451047182,
"acc_norm": 0.21428571428571427,
"acc_norm_stderr": 0.03670066451047182
},
"harness|hendrycksTest-global_facts|5": {
"acc": 0.2,
"acc_stderr": 0.04020151261036847,
"acc_norm": 0.2,
"acc_norm_stderr": 0.04020151261036847
},
"harness|hendrycksTest-high_school_biology|5": {
"acc": 0.1935483870967742,
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}
```
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
[More Information Needed]
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
[More Information Needed]
#### Who are the source data producers?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
[More Information Needed]
### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
[More Information Needed]
#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
[More Information Needed]
#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Dataset Card Authors [optional]
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## Dataset Card Contact
[More Information Needed] |
pvisnrt/special_samsum | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: id
dtype: string
- name: dialogue
sequence: string
- name: summary
sequence: string
- name: tags
sequence: string
- name: tag_ids
sequence: int64
splits:
- name: train
num_bytes: 20587448
num_examples: 14732
- name: test
num_bytes: 1153897
num_examples: 819
- name: validation
num_bytes: 1126310
num_examples: 818
download_size: 5893445
dataset_size: 22867655
---
# Dataset Card for "special_samsum"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
hon9kon9ize/yue-truthy | ---
language:
- zh
- yue
license: cc-by-4.0
dataset_info:
- config_name: yue
features:
- name: id
dtype: string
- name: source
dtype: string
- name: system
dtype: string
- name: prompt
dtype: string
- name: chosen
dtype: string
- name: rejected
dtype: string
splits:
- name: train
num_bytes: 1183319
num_examples: 1016
download_size: 733277
dataset_size: 1183319
- config_name: zh
features:
- name: id
dtype: string
- name: source
dtype: string
- name: system
dtype: string
- name: prompt
dtype: string
- name: chosen
dtype: string
- name: rejected
dtype: string
splits:
- name: train
num_bytes: 1171737
num_examples: 1016
download_size: 710265
dataset_size: 1171737
configs:
- config_name: yue
data_files:
- split: train
path: yue/train-*
- config_name: zh
data_files:
- split: train
path: zh/train-*
---
# Cantonese Truthy DPO
This dataset is a Cantonese and Simplified Chinese translation of [jondurbin/truthy-dpo-v0.1](https://huggingface.co/datasets/jondurbin/truthy-dpo-v0.1). For more detailed information about the original dataset, please refer to the provided link.
This dataset is translated by Gemini Pro and has not undergone any manual verification. The content may be inaccurate or misleading. please keep this in mind when using this dataset.
## License
This dataset is provided under the same license as the original dataset: CC BY 4.0
## Limitation and Usage Limits
Please check the original dataset for more information. |
m2af/ko-emotion-dataset | ---
language:
- ko
dataset_info:
features:
- name: created_date
dtype: string
- name: source
dtype: string
- name: context
dtype: string
- name: annotation
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 510197
num_examples: 1039
download_size: 150813
dataset_size: 510197
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# 한국어 감정 단문 데이터셋
## 데이터 개요
- 데이터 개수: 총 1039개
- 라벨러: (A, B, C, D, E)로 표시
- 단문 출처: X, Threads, Youtube, Naver Blog, Naver Cafe
## 감정 라벨 분류 표
- 중분류, 소분류로 구분
- 소분류의 대표 감정을 기준으로 구분
- 중분류 (총 9개)
- 기쁨, 사랑, 슬픔, 두려움, 분노, 미움(상대방), 욕망, 싫어함(상태), 수치심
- 소분류 (총 63개)
- 기쁨: 반가움, 즐거움, 신명남, 자신감, 감동, 만족감, 편안함, 고마움, 신뢰감, 안정감, 공감, 자랑스러움
- 사랑: 호감, 귀중함, 매력적, 두근거림, 아른거림, 너그러움, 열정적임, 다정함, 동정(슬픔)
- 슬픔: 억울함, 외로움, 후회, 실망, 허망, 그리움, 수치심, 고통, 절망, 무기력, 아픔
- 두려움: 위축감, 놀람, 공포, 걱정, 초조함
- 분노: 원망, 불쾌, 날카로움, 타오름
- 미움(상대방): 반감, 경멸, 비위상함, 치사함, 불신감, 시기심, 외면, 냉담
- 욕망: 욕심, 궁금함, 아쉬움, 불만, 갈등, 기대감
- 싫어함(상태): 답답함, 불편함, 난처함, 서먹함, 심심함, 싫증
- 수치심: 부끄러움, 죄책감, 미안함
## 활용
- Active Learning (감정 분류)
## Reference
- 조경은(2011). 서사구조의 자동 분석 기법을 통한 캐릭터 감성표현 모델 연구. 동국대학교 산학협력단
|
yzhuang/metatree_fri_c4_1000_25 | ---
dataset_info:
features:
- name: id
dtype: int64
- name: X
sequence: float64
- name: y
dtype: int64
splits:
- name: train
num_bytes: 161920
num_examples: 736
- name: validation
num_bytes: 58080
num_examples: 264
download_size: 254491
dataset_size: 220000
---
# Dataset Card for "metatree_fri_c4_1000_25"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Raul023/Paddy | ---
license: apache-2.0
---
|
erbacher/trivia_qa-halM | ---
dataset_info:
features:
- name: target
dtype: string
- name: query
dtype: string
- name: gold_generation
sequence: string
- name: text
dtype: string
- name: results
dtype: string
- name: em
dtype: float64
- name: hal_m
dtype: string
splits:
- name: train1
num_bytes: 36799502.40639716
num_examples: 39392
- name: train2
num_bytes: 36800436.59360284
num_examples: 39393
- name: dev
num_bytes: 8307250
num_examples: 8837
- name: test
num_bytes: 10650305
num_examples: 11313
download_size: 34799920
dataset_size: 92557494.0
---
# Dataset Card for "trivia_qa-halM"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
joey234/mmlu-sociology-neg-prepend | ---
dataset_info:
features:
- name: question
dtype: string
- name: choices
sequence: string
- name: answer
dtype:
class_label:
names:
'0': A
'1': B
'2': C
'3': D
- name: negate_openai_prompt
struct:
- name: content
dtype: string
- name: role
dtype: string
- name: neg_question
dtype: string
- name: fewshot_context
dtype: string
- name: ori_prompt
dtype: string
- name: neg_prompt
dtype: string
- name: fewshot_context_neg
dtype: string
- name: fewshot_context_ori
dtype: string
splits:
- name: dev
num_bytes: 7680
num_examples: 5
- name: test
num_bytes: 1913443
num_examples: 201
download_size: 229587
dataset_size: 1921123
configs:
- config_name: default
data_files:
- split: dev
path: data/dev-*
- split: test
path: data/test-*
---
# Dataset Card for "mmlu-sociology-neg-prepend"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
formospeech/nuu_sixian_hsu | ---
dataset_info:
config_name: train
features:
- name: id
dtype: string
- name: audio
dtype: audio
- name: duration
dtype: float64
- name: text
dtype: string
- name: ipa
dtype: string
- name: char_per_sec
dtype: float64
- name: speaker
dtype: string
splits:
- name: train
num_bytes: 60710889.0
num_examples: 775
download_size: 58806983
dataset_size: 60710889.0
configs:
- config_name: train
data_files:
- split: train
path: train/train-*
---
|
open-llm-leaderboard/details_The-Face-Of-Goonery__Huginn-22b-Prototype | ---
pretty_name: Evaluation run of The-Face-Of-Goonery/Huginn-22b-Prototype
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [The-Face-Of-Goonery/Huginn-22b-Prototype](https://huggingface.co/The-Face-Of-Goonery/Huginn-22b-Prototype)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 64 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 2 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the agregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_The-Face-Of-Goonery__Huginn-22b-Prototype\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-10-15T14:13:40.771756](https://huggingface.co/datasets/open-llm-leaderboard/details_The-Face-Of-Goonery__Huginn-22b-Prototype/blob/main/results_2023-10-15T14-13-40.771756.json)(note\
\ that their might be results for other tasks in the repos if successive evals didn't\
\ cover the same tasks. You find each in the results and the \"latest\" split for\
\ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.046665268456375836,\n\
\ \"em_stderr\": 0.0021600273157654512,\n \"f1\": 0.11504928691275146,\n\
\ \"f1_stderr\": 0.0025720161293884478,\n \"acc\": 0.36930437483133105,\n\
\ \"acc_stderr\": 0.008391006712261204\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.046665268456375836,\n \"em_stderr\": 0.0021600273157654512,\n\
\ \"f1\": 0.11504928691275146,\n \"f1_stderr\": 0.0025720161293884478\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.022744503411675512,\n \
\ \"acc_stderr\": 0.0041066206377496795\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.7158642462509865,\n \"acc_stderr\": 0.01267539278677273\n\
\ }\n}\n```"
repo_url: https://huggingface.co/The-Face-Of-Goonery/Huginn-22b-Prototype
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|arc:challenge|25_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_10_15T14_13_40.771756
path:
- '**/details_harness|drop|3_2023-10-15T14-13-40.771756.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-10-15T14-13-40.771756.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_10_15T14_13_40.771756
path:
- '**/details_harness|gsm8k|5_2023-10-15T14-13-40.771756.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-10-15T14-13-40.771756.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hellaswag|10_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-08-17T17:52:21.766212.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-management|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-virology|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- '**/details_harness|truthfulqa:mc|0_2023-08-17T17:52:21.766212.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-08-17T17:52:21.766212.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_10_15T14_13_40.771756
path:
- '**/details_harness|winogrande|5_2023-10-15T14-13-40.771756.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-10-15T14-13-40.771756.parquet'
- config_name: results
data_files:
- split: 2023_08_17T17_52_21.766212
path:
- results_2023-08-17T17:52:21.766212.parquet
- split: 2023_10_15T14_13_40.771756
path:
- results_2023-10-15T14-13-40.771756.parquet
- split: latest
path:
- results_2023-10-15T14-13-40.771756.parquet
---
# Dataset Card for Evaluation run of The-Face-Of-Goonery/Huginn-22b-Prototype
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/The-Face-Of-Goonery/Huginn-22b-Prototype
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** clementine@hf.co
### Dataset Summary
Dataset automatically created during the evaluation run of model [The-Face-Of-Goonery/Huginn-22b-Prototype](https://huggingface.co/The-Face-Of-Goonery/Huginn-22b-Prototype) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_The-Face-Of-Goonery__Huginn-22b-Prototype",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-10-15T14:13:40.771756](https://huggingface.co/datasets/open-llm-leaderboard/details_The-Face-Of-Goonery__Huginn-22b-Prototype/blob/main/results_2023-10-15T14-13-40.771756.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"em": 0.046665268456375836,
"em_stderr": 0.0021600273157654512,
"f1": 0.11504928691275146,
"f1_stderr": 0.0025720161293884478,
"acc": 0.36930437483133105,
"acc_stderr": 0.008391006712261204
},
"harness|drop|3": {
"em": 0.046665268456375836,
"em_stderr": 0.0021600273157654512,
"f1": 0.11504928691275146,
"f1_stderr": 0.0025720161293884478
},
"harness|gsm8k|5": {
"acc": 0.022744503411675512,
"acc_stderr": 0.0041066206377496795
},
"harness|winogrande|5": {
"acc": 0.7158642462509865,
"acc_stderr": 0.01267539278677273
}
}
```
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
[More Information Needed] |
manishiitg/ai2_arc | ---
dataset_info:
features:
- name: system
dtype: string
- name: instruction
dtype: string
- name: response
dtype: string
- name: lang
dtype: string
splits:
- name: train
num_bytes: 2318104
num_examples: 4502
download_size: 674650
dataset_size: 2318104
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
tyzhu/eval_tag_squad_v7 | ---
dataset_info:
features:
- name: id
dtype: string
- name: title
dtype: string
- name: context
dtype: string
- name: question
dtype: string
- name: answers
sequence:
- name: text
dtype: string
- name: answer_start
dtype: int32
- name: inputs
dtype: string
- name: targets
dtype: string
splits:
- name: train
num_bytes: 12876477
num_examples: 10570
- name: validation
num_bytes: 12876477
num_examples: 10570
download_size: 5563526
dataset_size: 25752954
---
# Dataset Card for "eval_tag_squad_v7"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
corey4593/H | ---
license: openrail
---
|
priyank-m/SROIE_2019_text_recognition | ---
annotations_creators: []
language:
- en
language_creators: []
license: []
multilinguality:
- monolingual
pretty_name: SROIE_2019_text_recognition
size_categories:
- 10K<n<100K
source_datasets: []
tags:
- text-recognition
- recognition
task_categories:
- image-to-text
task_ids:
- image-captioning
---
This dataset we prepared using the Scanned receipts OCR and information extraction(SROIE) dataset.
The SROIE dataset contains 973 scanned receipts in English language.
Cropping the bounding boxes from each of the receipts to generate this text-recognition dataset resulted in 33626 images for train set and 18704 images for the test set.
The text annotations for all the images inside a split are stored in a metadata.jsonl file.
usage:
from dataset import load_dataset
data = load_dataset("priyank-m/SROIE_2019_text_recognition")
source of raw SROIE dataset:
https://www.kaggle.com/datasets/urbikn/sroie-datasetv2 |
CyberHarem/panakeia_neuralcloud | ---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---
# Dataset of panakeia/パナケイア/帕那刻亚 (Neural Cloud)
This is the dataset of panakeia/パナケイア/帕那刻亚 (Neural Cloud), containing 18 images and their tags.
The core tags of this character are `long_hair, bangs, double_bun, hair_bun, ahoge, pink_hair, pink_eyes, bow, red_hair`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:----------|:----------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 18 | 23.38 MiB | [Download](https://huggingface.co/datasets/CyberHarem/panakeia_neuralcloud/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 18 | 15.58 MiB | [Download](https://huggingface.co/datasets/CyberHarem/panakeia_neuralcloud/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 40 | 30.62 MiB | [Download](https://huggingface.co/datasets/CyberHarem/panakeia_neuralcloud/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 18 | 22.10 MiB | [Download](https://huggingface.co/datasets/CyberHarem/panakeia_neuralcloud/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 40 | 40.56 MiB | [Download](https://huggingface.co/datasets/CyberHarem/panakeia_neuralcloud/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/panakeia_neuralcloud',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:-------------------------------------------------------------------------------------------------------------|
| 0 | 18 |  |  |  |  |  | looking_at_viewer, 1girl, solo, blush, shirt, open_mouth, jacket, skirt, holding, long_sleeves, off_shoulder |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | looking_at_viewer | 1girl | solo | blush | shirt | open_mouth | jacket | skirt | holding | long_sleeves | off_shoulder |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------|:--------|:-------|:--------|:--------|:-------------|:---------|:--------|:----------|:---------------|:---------------|
| 0 | 18 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X |
|
jha2ee/Sound_Spectrogram_Description | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 16182594.0
num_examples: 218
download_size: 16178537
dataset_size: 16182594.0
---
# Dataset Card for "Sound_Spectrogram_Description"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
DBQ/Burberry.Product.prices.Singapore | ---
annotations_creators:
- other
language_creators:
- other
language:
- en
license:
- unknown
multilinguality:
- monolingual
source_datasets:
- original
task_categories:
- text-classification
- image-classification
- feature-extraction
- image-segmentation
- image-to-image
- image-to-text
- object-detection
- summarization
- zero-shot-image-classification
pretty_name: Singapore - Burberry - Product-level price list
tags:
- webscraping
- ecommerce
- Burberry
- fashion
- fashion product
- image
- fashion image
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: website_name
dtype: string
- name: competence_date
dtype: string
- name: country_code
dtype: string
- name: currency_code
dtype: string
- name: brand
dtype: string
- name: category1_code
dtype: string
- name: category2_code
dtype: string
- name: category3_code
dtype: string
- name: product_code
dtype: int64
- name: title
dtype: string
- name: itemurl
dtype: string
- name: imageurl
dtype: string
- name: full_price
dtype: float64
- name: price
dtype: float64
- name: full_price_eur
dtype: float64
- name: price_eur
dtype: float64
- name: flg_discount
dtype: int64
splits:
- name: train
num_bytes: 856627
num_examples: 2691
download_size: 249890
dataset_size: 856627
---
# Burberry web scraped data
## About the website
The **luxury fashion industry** in the **Asia Pacific** region, particularly in **Singapore**, has flourished over the years, witnessing s significant surge in demand for high-end brands like **Burberry**. This growth is propelled by the increasing purchasing power and the evolving tastes of the growing middle class. Additionally, the rise of **Ecommerce** has enabled these brands to expand their reach further, making it easier for consumers to explore and purchase luxury goods. Therefore, the dataset observed pertains to the **Ecommerce product-list page (PLP) data on Burberry in Singapore**, offering insight into the digital consumer patterns related to the brand.
## Link to **dataset**
[Singapore - Burberry - Product-level price list dataset](https://www.databoutique.com/buy-data-page/Burberry%20Product-prices%20Singapore/r/rec3hYlcEwldAHk2N)
|
AdapterOcean/code_instructions_standardized_cluster_5_std | ---
dataset_info:
features:
- name: message
dtype: string
- name: message_type
dtype: string
- name: message_id
dtype: int64
- name: conversation_id
dtype: int64
- name: cluster
dtype: float64
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 30944001
num_examples: 28334
download_size: 15102966
dataset_size: 30944001
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "code_instructions_standardized_cluster_5_std"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
Kartheesh/MLdataset | ---
license: openrail
task_categories:
- question-answering
language:
- en
tags:
- climate
pretty_name: mountain
size_categories:
- 1M<n<10M
---
# Dataset Card for Dataset Name
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
[More Information Needed] |
Isamu136/big-animal-dataset-high-res-embedding | ---
dataset_info:
features:
- name: image
dtype: image
- name: caption
dtype: string
- name: l14_embeddings
sequence: float32
- name: moco_vitb_imagenet_embeddings
sequence: float32
- name: moco_vitb_imagenet_embeddings_without_last_layer
sequence: float32
- name: ibot_b_16_embedding
sequence: float32
- name: ibot_b_16_last_self_attn
sequence: float32
- name: midas_dpt_swin2_large_384
dtype: image
- name: subject_noun
dtype: string
splits:
- name: train
num_bytes: 3744432126.3
num_examples: 26180
download_size: 3795367998
dataset_size: 3744432126.3
---
# Dataset Card for "big-animal-dataset-high-res-embedding"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
one-sec-cv12/chunk_165 | ---
dataset_info:
features:
- name: audio
dtype:
audio:
sampling_rate: 16000
splits:
- name: train
num_bytes: 22107656304.375
num_examples: 230173
download_size: 20363526755
dataset_size: 22107656304.375
---
# Dataset Card for "chunk_165"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
freshpearYoon/train_free_60 | ---
dataset_info:
features:
- name: input_features
sequence:
sequence: float32
- name: labels
sequence: int64
splits:
- name: train
num_bytes: 9604557592
num_examples: 10000
download_size: 1272601883
dataset_size: 9604557592
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
Davlan/sib200 | ---
annotations_creators:
- found
language_creators:
- expert-generated
language:
- ace
- acm
- acq
- aeb
- af
- ajp
- ak
- als
- am
- apc
- ar
- ars
- ary
- arz
- as
- ast
- awa
- ayr
- azb
- azj
- ba
- bm
- ban
- be
- bem
- bn
- bho
- bjn
- bo
- bs
- bug
- bg
- ca
- ceb
- cs
- cjk
- ckb
- crh
- cy
- da
- de
- dik
- dyu
- dz
- el
- en
- eo
- et
- eu
- ee
- fo
- fj
- fi
- fon
- fr
- fur
- fuv
- gaz
- gd
- ga
- gl
- gn
- gu
- ht
- ha
- he
- hi
- hne
- hr
- hu
- hy
- ig
- ilo
- id
- is
- it
- jv
- ja
- kab
- kac
- kam
- kn
- ks
- ka
- kk
- kbp
- kea
- khk
- km
- ki
- rw
- ky
- kmb
- kmr
- knc
- kg
- ko
- lo
- lij
- li
- ln
- lt
- lmo
- ltg
- lb
- lua
- lg
- luo
- lus
- lvs
- mag
- mai
- ml
- mar
- min
- mk
- mt
- mni
- mos
- mi
- my
- nl
- nn
- nb
- npi
- nqo
- nso
- nus
- ny
- oc
- ory
- pag
- pa
- pap
- pbt
- pes
- plt
- pl
- pt
- prs
- quy
- ro
- rn
- ru
- sg
- sa
- sat
- scn
- shn
- si
- sk
- sl
- sm
- sn
- sd
- so
- st
- es
- sc
- sr
- ss
- su
- sv
- swh
- szl
- ta
- taq
- tt
- te
- tg
- tl
- th
- ti
- tpi
- tn
- ts
- tk
- tum
- tr
- tw
- tzm
- ug
- uk
- umb
- ur
- uzn
- vec
- vi
- war
- wo
- xh
- ydd
- yo
- yue
- zh
- zsm
- zu
license:
- cc-by-sa-4.0
multilinguality:
- multilingual
pretty_name: sib200
language_details: ace_Arab, ace_Latn, acm_Arab, acq_Arab, aeb_Arab, afr_Latn, ajp_Arab,
aka_Latn, amh_Ethi, apc_Arab, arb_Arab, ars_Arab, ary_Arab, arz_Arab, asm_Beng,
ast_Latn, awa_Deva, ayr_Latn, azb_Arab, azj_Latn, bak_Cyrl, bam_Latn, ban_Latn,bel_Cyrl,
bem_Latn, ben_Beng, bho_Deva, bjn_Arab, bjn_Latn, bod_Tibt, bos_Latn, bug_Latn,
bul_Cyrl, cat_Latn, ceb_Latn, ces_Latn, cjk_Latn, ckb_Arab, crh_Latn, cym_Latn,
dan_Latn, deu_Latn, dik_Latn, dyu_Latn, dzo_Tibt, ell_Grek, eng_Latn, epo_Latn,
est_Latn, eus_Latn, ewe_Latn, fao_Latn, pes_Arab, fij_Latn, fin_Latn, fon_Latn,
fra_Latn, fur_Latn, fuv_Latn, gla_Latn, gle_Latn, glg_Latn, grn_Latn, guj_Gujr,
hat_Latn, hau_Latn, heb_Hebr, hin_Deva, hne_Deva, hrv_Latn, hun_Latn, hye_Armn,
ibo_Latn, ilo_Latn, ind_Latn, isl_Latn, ita_Latn, jav_Latn, jpn_Jpan, kab_Latn,
kac_Latn, kam_Latn, kan_Knda, kas_Arab, kas_Deva, kat_Geor, knc_Arab, knc_Latn,
kaz_Cyrl, kbp_Latn, kea_Latn, khm_Khmr, kik_Latn, kin_Latn, kir_Cyrl, kmb_Latn,
kon_Latn, kor_Hang, kmr_Latn, lao_Laoo, lvs_Latn, lij_Latn, lim_Latn, lin_Latn,
lit_Latn, lmo_Latn, ltg_Latn, ltz_Latn, lua_Latn, lug_Latn, luo_Latn, lus_Latn,
mag_Deva, mai_Deva, mal_Mlym, mar_Deva, min_Latn, mkd_Cyrl, plt_Latn, mlt_Latn,
mni_Beng, khk_Cyrl, mos_Latn, mri_Latn, zsm_Latn, mya_Mymr, nld_Latn, nno_Latn,
nob_Latn, npi_Deva, nso_Latn, nus_Latn, nya_Latn, oci_Latn, gaz_Latn, ory_Orya,
pag_Latn, pan_Guru, pap_Latn, pol_Latn, por_Latn, prs_Arab, pbt_Arab, quy_Latn,
ron_Latn, run_Latn, rus_Cyrl, sag_Latn, san_Deva, sat_Beng, scn_Latn, shn_Mymr,
sin_Sinh, slk_Latn, slv_Latn, smo_Latn, sna_Latn, snd_Arab, som_Latn, sot_Latn,
spa_Latn, als_Latn, srd_Latn, srp_Cyrl, ssw_Latn, sun_Latn, swe_Latn, swh_Latn,
szl_Latn, tam_Taml, tat_Cyrl, tel_Telu, tgk_Cyrl, tgl_Latn, tha_Thai, tir_Ethi,
taq_Latn, taq_Tfng, tpi_Latn, tsn_Latn, tso_Latn, tuk_Latn, tum_Latn, tur_Latn,
twi_Latn, tzm_Tfng, uig_Arab, ukr_Cyrl, umb_Latn, urd_Arab, uzn_Latn, vec_Latn,
vie_Latn, war_Latn, wol_Latn, xho_Latn, ydd_Hebr, yor_Latn, yue_Hant, zho_Hans,
zho_Hant, zul_Latn
size_categories:
- 1K<n<10K
source_datasets:
- original
tags:
- news-topic
- sib-200
- sib200
task_categories:
- text-classification
task_ids:
- topic-classification
configs:
- config_name: ace_Arab
data_files:
- split: train
path: data/ace_Arab/train.tsv
- split: validation
path: data/ace_Arab/dev.tsv
- split: test
path: data/ace_Arab/test.tsv
- config_name: ace_Latn
data_files:
- split: train
path: data/ace_Latn/train.tsv
- split: validation
path: data/ace_Latn/dev.tsv
- split: test
path: data/ace_Latn/test.tsv
- config_name: acm_Arab
data_files:
- split: train
path: data/acm_Arab/train.tsv
- split: validation
path: data/acm_Arab/dev.tsv
- split: test
path: data/acm_Arab/test.tsv
- config_name: acq_Arab
data_files:
- split: train
path: data/acq_Arab/train.tsv
- split: validation
path: data/acq_Arab/dev.tsv
- split: test
path: data/acq_Arab/test.tsv
- config_name: aeb_Arab
data_files:
- split: train
path: data/aeb_Arab/train.tsv
- split: validation
path: data/aeb_Arab/dev.tsv
- split: test
path: data/aeb_Arab/test.tsv
- config_name: afr_Latn
data_files:
- split: train
path: data/afr_Latn/train.tsv
- split: validation
path: data/afr_Latn/dev.tsv
- split: test
path: data/afr_Latn/test.tsv
- config_name: ajp_Arab
data_files:
- split: train
path: data/ajp_Arab/train.tsv
- split: validation
path: data/ajp_Arab/dev.tsv
- split: test
path: data/ajp_Arab/test.tsv
- config_name: aka_Latn
data_files:
- split: train
path: data/aka_Latn/train.tsv
- split: validation
path: data/aka_Latn/dev.tsv
- split: test
path: data/aka_Latn/test.tsv
- config_name: als_Latn
data_files:
- split: train
path: data/als_Latn/train.tsv
- split: validation
path: data/als_Latn/dev.tsv
- split: test
path: data/als_Latn/test.tsv
- config_name: amh_Ethi
data_files:
- split: train
path: data/amh_Ethi/train.tsv
- split: validation
path: data/amh_Ethi/dev.tsv
- split: test
path: data/amh_Ethi/test.tsv
- config_name: apc_Arab
data_files:
- split: train
path: data/apc_Arab/train.tsv
- split: validation
path: data/apc_Arab/dev.tsv
- split: test
path: data/apc_Arab/test.tsv
- config_name: arb_Arab
data_files:
- split: train
path: data/arb_Arab/train.tsv
- split: validation
path: data/arb_Arab/dev.tsv
- split: test
path: data/arb_Arab/test.tsv
- config_name: arb_Latn
data_files:
- split: train
path: data/arb_Latn/train.tsv
- split: validation
path: data/arb_Latn/dev.tsv
- split: test
path: data/arb_Latn/test.tsv
- config_name: ars_Arab
data_files:
- split: train
path: data/ars_Arab/train.tsv
- split: validation
path: data/ars_Arab/dev.tsv
- split: test
path: data/ars_Arab/test.tsv
- config_name: ary_Arab
data_files:
- split: train
path: data/ary_Arab/train.tsv
- split: validation
path: data/ary_Arab/dev.tsv
- split: test
path: data/ary_Arab/test.tsv
- config_name: arz_Arab
data_files:
- split: train
path: data/arz_Arab/train.tsv
- split: validation
path: data/arz_Arab/dev.tsv
- split: test
path: data/arz_Arab/test.tsv
- config_name: asm_Beng
data_files:
- split: train
path: data/asm_Beng/train.tsv
- split: validation
path: data/asm_Beng/dev.tsv
- split: test
path: data/asm_Beng/test.tsv
- config_name: ast_Latn
data_files:
- split: train
path: data/ast_Latn/train.tsv
- split: validation
path: data/ast_Latn/dev.tsv
- split: test
path: data/ast_Latn/test.tsv
- config_name: awa_Deva
data_files:
- split: train
path: data/awa_Deva/train.tsv
- split: validation
path: data/awa_Deva/dev.tsv
- split: test
path: data/awa_Deva/test.tsv
- config_name: ayr_Latn
data_files:
- split: train
path: data/ayr_Latn/train.tsv
- split: validation
path: data/ayr_Latn/dev.tsv
- split: test
path: data/ayr_Latn/test.tsv
- config_name: azb_Arab
data_files:
- split: train
path: data/azb_Arab/train.tsv
- split: validation
path: data/azb_Arab/dev.tsv
- split: test
path: data/azb_Arab/test.tsv
- config_name: azj_Latn
data_files:
- split: train
path: data/azj_Latn/train.tsv
- split: validation
path: data/azj_Latn/dev.tsv
- split: test
path: data/azj_Latn/test.tsv
- config_name: bak_Cyrl
data_files:
- split: train
path: data/bak_Cyrl/train.tsv
- split: validation
path: data/bak_Cyrl/dev.tsv
- split: test
path: data/bak_Cyrl/test.tsv
- config_name: bam_Latn
data_files:
- split: train
path: data/bam_Latn/train.tsv
- split: validation
path: data/bam_Latn/dev.tsv
- split: test
path: data/bam_Latn/test.tsv
- config_name: ban_Latn
data_files:
- split: train
path: data/ban_Latn/train.tsv
- split: validation
path: data/ban_Latn/dev.tsv
- split: test
path: data/ban_Latn/test.tsv
- config_name: bel_Cyrl
data_files:
- split: train
path: data/bel_Cyrl/train.tsv
- split: validation
path: data/bel_Cyrl/dev.tsv
- split: test
path: data/bel_Cyrl/test.tsv
- config_name: bem_Latn
data_files:
- split: train
path: data/bem_Latn/train.tsv
- split: validation
path: data/bem_Latn/dev.tsv
- split: test
path: data/bem_Latn/test.tsv
- config_name: ben_Beng
data_files:
- split: train
path: data/ben_Beng/train.tsv
- split: validation
path: data/ben_Beng/dev.tsv
- split: test
path: data/ben_Beng/test.tsv
- config_name: bho_Deva
data_files:
- split: train
path: data/bho_Deva/train.tsv
- split: validation
path: data/bho_Deva/dev.tsv
- split: test
path: data/bho_Deva/test.tsv
- config_name: bjn_Arab
data_files:
- split: train
path: data/bjn_Arab/train.tsv
- split: validation
path: data/bjn_Arab/dev.tsv
- split: test
path: data/bjn_Arab/test.tsv
- config_name: bjn_Latn
data_files:
- split: train
path: data/bjn_Latn/train.tsv
- split: validation
path: data/bjn_Latn/dev.tsv
- split: test
path: data/bjn_Latn/test.tsv
- config_name: bod_Tibt
data_files:
- split: train
path: data/bod_Tibt/train.tsv
- split: validation
path: data/bod_Tibt/dev.tsv
- split: test
path: data/bod_Tibt/test.tsv
- config_name: bos_Latn
data_files:
- split: train
path: data/bos_Latn/train.tsv
- split: validation
path: data/bos_Latn/dev.tsv
- split: test
path: data/bos_Latn/test.tsv
- config_name: bug_Latn
data_files:
- split: train
path: data/bug_Latn/train.tsv
- split: validation
path: data/bug_Latn/dev.tsv
- split: test
path: data/bug_Latn/test.tsv
- config_name: bul_Cyrl
data_files:
- split: train
path: data/bul_Cyrl/train.tsv
- split: validation
path: data/bul_Cyrl/dev.tsv
- split: test
path: data/bul_Cyrl/test.tsv
- config_name: cat_Latn
data_files:
- split: train
path: data/cat_Latn/train.tsv
- split: validation
path: data/cat_Latn/dev.tsv
- split: test
path: data/cat_Latn/test.tsv
- config_name: ceb_Latn
data_files:
- split: train
path: data/ceb_Latn/train.tsv
- split: validation
path: data/ceb_Latn/dev.tsv
- split: test
path: data/ceb_Latn/test.tsv
- config_name: ces_Latn
data_files:
- split: train
path: data/ces_Latn/train.tsv
- split: validation
path: data/ces_Latn/dev.tsv
- split: test
path: data/ces_Latn/test.tsv
- config_name: cjk_Latn
data_files:
- split: train
path: data/cjk_Latn/train.tsv
- split: validation
path: data/cjk_Latn/dev.tsv
- split: test
path: data/cjk_Latn/test.tsv
- config_name: ckb_Arab
data_files:
- split: train
path: data/ckb_Arab/train.tsv
- split: validation
path: data/ckb_Arab/dev.tsv
- split: test
path: data/ckb_Arab/test.tsv
- config_name: crh_Latn
data_files:
- split: train
path: data/crh_Latn/train.tsv
- split: validation
path: data/crh_Latn/dev.tsv
- split: test
path: data/crh_Latn/test.tsv
- config_name: cym_Latn
data_files:
- split: train
path: data/cym_Latn/train.tsv
- split: validation
path: data/cym_Latn/dev.tsv
- split: test
path: data/cym_Latn/test.tsv
- config_name: dan_Latn
data_files:
- split: train
path: data/dan_Latn/train.tsv
- split: validation
path: data/dan_Latn/dev.tsv
- split: test
path: data/dan_Latn/test.tsv
- config_name: deu_Latn
data_files:
- split: train
path: data/deu_Latn/train.tsv
- split: validation
path: data/deu_Latn/dev.tsv
- split: test
path: data/deu_Latn/test.tsv
- config_name: dik_Latn
data_files:
- split: train
path: data/dik_Latn/train.tsv
- split: validation
path: data/dik_Latn/dev.tsv
- split: test
path: data/dik_Latn/test.tsv
- config_name: dyu_Latn
data_files:
- split: train
path: data/dyu_Latn/train.tsv
- split: validation
path: data/dyu_Latn/dev.tsv
- split: test
path: data/dyu_Latn/test.tsv
- config_name: dzo_Tibt
data_files:
- split: train
path: data/dzo_Tibt/train.tsv
- split: validation
path: data/dzo_Tibt/dev.tsv
- split: test
path: data/dzo_Tibt/test.tsv
- config_name: ell_Grek
data_files:
- split: train
path: data/ell_Grek/train.tsv
- split: validation
path: data/ell_Grek/dev.tsv
- split: test
path: data/ell_Grek/test.tsv
- config_name: eng_Latn
data_files:
- split: train
path: data/eng_Latn/train.tsv
- split: validation
path: data/eng_Latn/dev.tsv
- split: test
path: data/eng_Latn/test.tsv
- config_name: epo_Latn
data_files:
- split: train
path: data/epo_Latn/train.tsv
- split: validation
path: data/epo_Latn/dev.tsv
- split: test
path: data/epo_Latn/test.tsv
- config_name: est_Latn
data_files:
- split: train
path: data/est_Latn/train.tsv
- split: validation
path: data/est_Latn/dev.tsv
- split: test
path: data/est_Latn/test.tsv
- config_name: eus_Latn
data_files:
- split: train
path: data/eus_Latn/train.tsv
- split: validation
path: data/eus_Latn/dev.tsv
- split: test
path: data/eus_Latn/test.tsv
- config_name: ewe_Latn
data_files:
- split: train
path: data/ewe_Latn/train.tsv
- split: validation
path: data/ewe_Latn/dev.tsv
- split: test
path: data/ewe_Latn/test.tsv
- config_name: fao_Latn
data_files:
- split: train
path: data/fao_Latn/train.tsv
- split: validation
path: data/fao_Latn/dev.tsv
- split: test
path: data/fao_Latn/test.tsv
- config_name: fij_Latn
data_files:
- split: train
path: data/fij_Latn/train.tsv
- split: validation
path: data/fij_Latn/dev.tsv
- split: test
path: data/fij_Latn/test.tsv
- config_name: fin_Latn
data_files:
- split: train
path: data/fin_Latn/train.tsv
- split: validation
path: data/fin_Latn/dev.tsv
- split: test
path: data/fin_Latn/test.tsv
- config_name: fon_Latn
data_files:
- split: train
path: data/fon_Latn/train.tsv
- split: validation
path: data/fon_Latn/dev.tsv
- split: test
path: data/fon_Latn/test.tsv
- config_name: fra_Latn
data_files:
- split: train
path: data/fra_Latn/train.tsv
- split: validation
path: data/fra_Latn/dev.tsv
- split: test
path: data/fra_Latn/test.tsv
- config_name: fur_Latn
data_files:
- split: train
path: data/fur_Latn/train.tsv
- split: validation
path: data/fur_Latn/dev.tsv
- split: test
path: data/fur_Latn/test.tsv
- config_name: fuv_Latn
data_files:
- split: train
path: data/fuv_Latn/train.tsv
- split: validation
path: data/fuv_Latn/dev.tsv
- split: test
path: data/fuv_Latn/test.tsv
- config_name: gaz_Latn
data_files:
- split: train
path: data/gaz_Latn/train.tsv
- split: validation
path: data/gaz_Latn/dev.tsv
- split: test
path: data/gaz_Latn/test.tsv
- config_name: gla_Latn
data_files:
- split: train
path: data/gla_Latn/train.tsv
- split: validation
path: data/gla_Latn/dev.tsv
- split: test
path: data/gla_Latn/test.tsv
- config_name: gle_Latn
data_files:
- split: train
path: data/gle_Latn/train.tsv
- split: validation
path: data/gle_Latn/dev.tsv
- split: test
path: data/gle_Latn/test.tsv
- config_name: glg_Latn
data_files:
- split: train
path: data/glg_Latn/train.tsv
- split: validation
path: data/glg_Latn/dev.tsv
- split: test
path: data/glg_Latn/test.tsv
- config_name: grn_Latn
data_files:
- split: train
path: data/grn_Latn/train.tsv
- split: validation
path: data/grn_Latn/dev.tsv
- split: test
path: data/grn_Latn/test.tsv
- config_name: guj_Gujr
data_files:
- split: train
path: data/guj_Gujr/train.tsv
- split: validation
path: data/guj_Gujr/dev.tsv
- split: test
path: data/guj_Gujr/test.tsv
- config_name: hat_Latn
data_files:
- split: train
path: data/hat_Latn/train.tsv
- split: validation
path: data/hat_Latn/dev.tsv
- split: test
path: data/hat_Latn/test.tsv
- config_name: hau_Latn
data_files:
- split: train
path: data/hau_Latn/train.tsv
- split: validation
path: data/hau_Latn/dev.tsv
- split: test
path: data/hau_Latn/test.tsv
- config_name: heb_Hebr
data_files:
- split: train
path: data/heb_Hebr/train.tsv
- split: validation
path: data/heb_Hebr/dev.tsv
- split: test
path: data/heb_Hebr/test.tsv
- config_name: hin_Deva
data_files:
- split: train
path: data/hin_Deva/train.tsv
- split: validation
path: data/hin_Deva/dev.tsv
- split: test
path: data/hin_Deva/test.tsv
- config_name: hne_Deva
data_files:
- split: train
path: data/hne_Deva/train.tsv
- split: validation
path: data/hne_Deva/dev.tsv
- split: test
path: data/hne_Deva/test.tsv
- config_name: hrv_Latn
data_files:
- split: train
path: data/hrv_Latn/train.tsv
- split: validation
path: data/hrv_Latn/dev.tsv
- split: test
path: data/hrv_Latn/test.tsv
- config_name: hun_Latn
data_files:
- split: train
path: data/hun_Latn/train.tsv
- split: validation
path: data/hun_Latn/dev.tsv
- split: test
path: data/hun_Latn/test.tsv
- config_name: hye_Armn
data_files:
- split: train
path: data/hye_Armn/train.tsv
- split: validation
path: data/hye_Armn/dev.tsv
- split: test
path: data/hye_Armn/test.tsv
- config_name: ibo_Latn
data_files:
- split: train
path: data/ibo_Latn/train.tsv
- split: validation
path: data/ibo_Latn/dev.tsv
- split: test
path: data/ibo_Latn/test.tsv
- config_name: ilo_Latn
data_files:
- split: train
path: data/ilo_Latn/train.tsv
- split: validation
path: data/ilo_Latn/dev.tsv
- split: test
path: data/ilo_Latn/test.tsv
- config_name: ind_Latn
data_files:
- split: train
path: data/ind_Latn/train.tsv
- split: validation
path: data/ind_Latn/dev.tsv
- split: test
path: data/ind_Latn/test.tsv
- config_name: isl_Latn
data_files:
- split: train
path: data/isl_Latn/train.tsv
- split: validation
path: data/isl_Latn/dev.tsv
- split: test
path: data/isl_Latn/test.tsv
- config_name: ita_Latn
data_files:
- split: train
path: data/ita_Latn/train.tsv
- split: validation
path: data/ita_Latn/dev.tsv
- split: test
path: data/ita_Latn/test.tsv
- config_name: jav_Latn
data_files:
- split: train
path: data/jav_Latn/train.tsv
- split: validation
path: data/jav_Latn/dev.tsv
- split: test
path: data/jav_Latn/test.tsv
- config_name: jpn_Jpan
data_files:
- split: train
path: data/jpn_Jpan/train.tsv
- split: validation
path: data/jpn_Jpan/dev.tsv
- split: test
path: data/jpn_Jpan/test.tsv
- config_name: kab_Latn
data_files:
- split: train
path: data/kab_Latn/train.tsv
- split: validation
path: data/kab_Latn/dev.tsv
- split: test
path: data/kab_Latn/test.tsv
- config_name: kac_Latn
data_files:
- split: train
path: data/kac_Latn/train.tsv
- split: validation
path: data/kac_Latn/dev.tsv
- split: test
path: data/kac_Latn/test.tsv
- config_name: kam_Latn
data_files:
- split: train
path: data/kam_Latn/train.tsv
- split: validation
path: data/kam_Latn/dev.tsv
- split: test
path: data/kam_Latn/test.tsv
- config_name: kan_Knda
data_files:
- split: train
path: data/kan_Knda/train.tsv
- split: validation
path: data/kan_Knda/dev.tsv
- split: test
path: data/kan_Knda/test.tsv
- config_name: kas_Arab
data_files:
- split: train
path: data/kas_Arab/train.tsv
- split: validation
path: data/kas_Arab/dev.tsv
- split: test
path: data/kas_Arab/test.tsv
- config_name: kas_Deva
data_files:
- split: train
path: data/kas_Deva/train.tsv
- split: validation
path: data/kas_Deva/dev.tsv
- split: test
path: data/kas_Deva/test.tsv
- config_name: kat_Geor
data_files:
- split: train
path: data/kat_Geor/train.tsv
- split: validation
path: data/kat_Geor/dev.tsv
- split: test
path: data/kat_Geor/test.tsv
- config_name: kaz_Cyrl
data_files:
- split: train
path: data/kaz_Cyrl/train.tsv
- split: validation
path: data/kaz_Cyrl/dev.tsv
- split: test
path: data/kaz_Cyrl/test.tsv
- config_name: kbp_Latn
data_files:
- split: train
path: data/kbp_Latn/train.tsv
- split: validation
path: data/kbp_Latn/dev.tsv
- split: test
path: data/kbp_Latn/test.tsv
- config_name: kea_Latn
data_files:
- split: train
path: data/kea_Latn/train.tsv
- split: validation
path: data/kea_Latn/dev.tsv
- split: test
path: data/kea_Latn/test.tsv
- config_name: khk_Cyrl
data_files:
- split: train
path: data/khk_Cyrl/train.tsv
- split: validation
path: data/khk_Cyrl/dev.tsv
- split: test
path: data/khk_Cyrl/test.tsv
- config_name: khm_Khmr
data_files:
- split: train
path: data/khm_Khmr/train.tsv
- split: validation
path: data/khm_Khmr/dev.tsv
- split: test
path: data/khm_Khmr/test.tsv
- config_name: kik_Latn
data_files:
- split: train
path: data/kik_Latn/train.tsv
- split: validation
path: data/kik_Latn/dev.tsv
- split: test
path: data/kik_Latn/test.tsv
- config_name: kin_Latn
data_files:
- split: train
path: data/kin_Latn/train.tsv
- split: validation
path: data/kin_Latn/dev.tsv
- split: test
path: data/kin_Latn/test.tsv
- config_name: kir_Cyrl
data_files:
- split: train
path: data/kir_Cyrl/train.tsv
- split: validation
path: data/kir_Cyrl/dev.tsv
- split: test
path: data/kir_Cyrl/test.tsv
- config_name: kmb_Latn
data_files:
- split: train
path: data/kmb_Latn/train.tsv
- split: validation
path: data/kmb_Latn/dev.tsv
- split: test
path: data/kmb_Latn/test.tsv
- config_name: kmr_Latn
data_files:
- split: train
path: data/kmr_Latn/train.tsv
- split: validation
path: data/kmr_Latn/dev.tsv
- split: test
path: data/kmr_Latn/test.tsv
- config_name: knc_Arab
data_files:
- split: train
path: data/knc_Arab/train.tsv
- split: validation
path: data/knc_Arab/dev.tsv
- split: test
path: data/knc_Arab/test.tsv
- config_name: knc_Latn
data_files:
- split: train
path: data/knc_Latn/train.tsv
- split: validation
path: data/knc_Latn/dev.tsv
- split: test
path: data/knc_Latn/test.tsv
- config_name: kon_Latn
data_files:
- split: train
path: data/kon_Latn/train.tsv
- split: validation
path: data/kon_Latn/dev.tsv
- split: test
path: data/kon_Latn/test.tsv
- config_name: kor_Hang
data_files:
- split: train
path: data/kor_Hang/train.tsv
- split: validation
path: data/kor_Hang/dev.tsv
- split: test
path: data/kor_Hang/test.tsv
- config_name: lao_Laoo
data_files:
- split: train
path: data/lao_Laoo/train.tsv
- split: validation
path: data/lao_Laoo/dev.tsv
- split: test
path: data/lao_Laoo/test.tsv
- config_name: lij_Latn
data_files:
- split: train
path: data/lij_Latn/train.tsv
- split: validation
path: data/lij_Latn/dev.tsv
- split: test
path: data/lij_Latn/test.tsv
- config_name: lim_Latn
data_files:
- split: train
path: data/lim_Latn/train.tsv
- split: validation
path: data/lim_Latn/dev.tsv
- split: test
path: data/lim_Latn/test.tsv
- config_name: lin_Latn
data_files:
- split: train
path: data/lin_Latn/train.tsv
- split: validation
path: data/lin_Latn/dev.tsv
- split: test
path: data/lin_Latn/test.tsv
- config_name: lit_Latn
data_files:
- split: train
path: data/lit_Latn/train.tsv
- split: validation
path: data/lit_Latn/dev.tsv
- split: test
path: data/lit_Latn/test.tsv
- config_name: lmo_Latn
data_files:
- split: train
path: data/lmo_Latn/train.tsv
- split: validation
path: data/lmo_Latn/dev.tsv
- split: test
path: data/lmo_Latn/test.tsv
- config_name: ltg_Latn
data_files:
- split: train
path: data/ltg_Latn/train.tsv
- split: validation
path: data/ltg_Latn/dev.tsv
- split: test
path: data/ltg_Latn/test.tsv
- config_name: ltz_Latn
data_files:
- split: train
path: data/ltz_Latn/train.tsv
- split: validation
path: data/ltz_Latn/dev.tsv
- split: test
path: data/ltz_Latn/test.tsv
- config_name: lua_Latn
data_files:
- split: train
path: data/lua_Latn/train.tsv
- split: validation
path: data/lua_Latn/dev.tsv
- split: test
path: data/lua_Latn/test.tsv
- config_name: lug_Latn
data_files:
- split: train
path: data/lug_Latn/train.tsv
- split: validation
path: data/lug_Latn/dev.tsv
- split: test
path: data/lug_Latn/test.tsv
- config_name: luo_Latn
data_files:
- split: train
path: data/luo_Latn/train.tsv
- split: validation
path: data/luo_Latn/dev.tsv
- split: test
path: data/luo_Latn/test.tsv
- config_name: lus_Latn
data_files:
- split: train
path: data/lus_Latn/train.tsv
- split: validation
path: data/lus_Latn/dev.tsv
- split: test
path: data/lus_Latn/test.tsv
- config_name: lvs_Latn
data_files:
- split: train
path: data/lvs_Latn/train.tsv
- split: validation
path: data/lvs_Latn/dev.tsv
- split: test
path: data/lvs_Latn/test.tsv
- config_name: mag_Deva
data_files:
- split: train
path: data/mag_Deva/train.tsv
- split: validation
path: data/mag_Deva/dev.tsv
- split: test
path: data/mag_Deva/test.tsv
- config_name: mai_Deva
data_files:
- split: train
path: data/mai_Deva/train.tsv
- split: validation
path: data/mai_Deva/dev.tsv
- split: test
path: data/mai_Deva/test.tsv
- config_name: mal_Mlym
data_files:
- split: train
path: data/mal_Mlym/train.tsv
- split: validation
path: data/mal_Mlym/dev.tsv
- split: test
path: data/mal_Mlym/test.tsv
- config_name: mar_Deva
data_files:
- split: train
path: data/mar_Deva/train.tsv
- split: validation
path: data/mar_Deva/dev.tsv
- split: test
path: data/mar_Deva/test.tsv
- config_name: min_Arab
data_files:
- split: train
path: data/min_Arab/train.tsv
- split: validation
path: data/min_Arab/dev.tsv
- split: test
path: data/min_Arab/test.tsv
- config_name: min_Latn
data_files:
- split: train
path: data/min_Latn/train.tsv
- split: validation
path: data/min_Latn/dev.tsv
- split: test
path: data/min_Latn/test.tsv
- config_name: mkd_Cyrl
data_files:
- split: train
path: data/mkd_Cyrl/train.tsv
- split: validation
path: data/mkd_Cyrl/dev.tsv
- split: test
path: data/mkd_Cyrl/test.tsv
- config_name: mlt_Latn
data_files:
- split: train
path: data/mlt_Latn/train.tsv
- split: validation
path: data/mlt_Latn/dev.tsv
- split: test
path: data/mlt_Latn/test.tsv
- config_name: mni_Beng
data_files:
- split: train
path: data/mni_Beng/train.tsv
- split: validation
path: data/mni_Beng/dev.tsv
- split: test
path: data/mni_Beng/test.tsv
- config_name: mos_Latn
data_files:
- split: train
path: data/mos_Latn/train.tsv
- split: validation
path: data/mos_Latn/dev.tsv
- split: test
path: data/mos_Latn/test.tsv
- config_name: mri_Latn
data_files:
- split: train
path: data/mri_Latn/train.tsv
- split: validation
path: data/mri_Latn/dev.tsv
- split: test
path: data/mri_Latn/test.tsv
- config_name: mya_Mymr
data_files:
- split: train
path: data/mya_Mymr/train.tsv
- split: validation
path: data/mya_Mymr/dev.tsv
- split: test
path: data/mya_Mymr/test.tsv
- config_name: nld_Latn
data_files:
- split: train
path: data/nld_Latn/train.tsv
- split: validation
path: data/nld_Latn/dev.tsv
- split: test
path: data/nld_Latn/test.tsv
- config_name: nno_Latn
data_files:
- split: train
path: data/nno_Latn/train.tsv
- split: validation
path: data/nno_Latn/dev.tsv
- split: test
path: data/nno_Latn/test.tsv
- config_name: nob_Latn
data_files:
- split: train
path: data/nob_Latn/train.tsv
- split: validation
path: data/nob_Latn/dev.tsv
- split: test
path: data/nob_Latn/test.tsv
- config_name: npi_Deva
data_files:
- split: train
path: data/npi_Deva/train.tsv
- split: validation
path: data/npi_Deva/dev.tsv
- split: test
path: data/npi_Deva/test.tsv
- config_name: nqo_Nkoo
data_files:
- split: train
path: data/nqo_Nkoo/train.tsv
- split: validation
path: data/nqo_Nkoo/dev.tsv
- split: test
path: data/nqo_Nkoo/test.tsv
- config_name: nqo_Nkoo.zip
data_files:
- split: train
path: data/nqo_Nkoo.zip/train.tsv
- split: validation
path: data/nqo_Nkoo.zip/dev.tsv
- split: test
path: data/nqo_Nkoo.zip/test.tsv
- config_name: nso_Latn
data_files:
- split: train
path: data/nso_Latn/train.tsv
- split: validation
path: data/nso_Latn/dev.tsv
- split: test
path: data/nso_Latn/test.tsv
- config_name: nus_Latn
data_files:
- split: train
path: data/nus_Latn/train.tsv
- split: validation
path: data/nus_Latn/dev.tsv
- split: test
path: data/nus_Latn/test.tsv
- config_name: nya_Latn
data_files:
- split: train
path: data/nya_Latn/train.tsv
- split: validation
path: data/nya_Latn/dev.tsv
- split: test
path: data/nya_Latn/test.tsv
- config_name: oci_Latn
data_files:
- split: train
path: data/oci_Latn/train.tsv
- split: validation
path: data/oci_Latn/dev.tsv
- split: test
path: data/oci_Latn/test.tsv
- config_name: ory_Orya
data_files:
- split: train
path: data/ory_Orya/train.tsv
- split: validation
path: data/ory_Orya/dev.tsv
- split: test
path: data/ory_Orya/test.tsv
- config_name: pag_Latn
data_files:
- split: train
path: data/pag_Latn/train.tsv
- split: validation
path: data/pag_Latn/dev.tsv
- split: test
path: data/pag_Latn/test.tsv
- config_name: pan_Guru
data_files:
- split: train
path: data/pan_Guru/train.tsv
- split: validation
path: data/pan_Guru/dev.tsv
- split: test
path: data/pan_Guru/test.tsv
- config_name: pap_Latn
data_files:
- split: train
path: data/pap_Latn/train.tsv
- split: validation
path: data/pap_Latn/dev.tsv
- split: test
path: data/pap_Latn/test.tsv
- config_name: pbt_Arab
data_files:
- split: train
path: data/pbt_Arab/train.tsv
- split: validation
path: data/pbt_Arab/dev.tsv
- split: test
path: data/pbt_Arab/test.tsv
- config_name: pes_Arab
data_files:
- split: train
path: data/pes_Arab/train.tsv
- split: validation
path: data/pes_Arab/dev.tsv
- split: test
path: data/pes_Arab/test.tsv
- config_name: plt_Latn
data_files:
- split: train
path: data/plt_Latn/train.tsv
- split: validation
path: data/plt_Latn/dev.tsv
- split: test
path: data/plt_Latn/test.tsv
- config_name: pol_Latn
data_files:
- split: train
path: data/pol_Latn/train.tsv
- split: validation
path: data/pol_Latn/dev.tsv
- split: test
path: data/pol_Latn/test.tsv
- config_name: por_Latn
data_files:
- split: train
path: data/por_Latn/train.tsv
- split: validation
path: data/por_Latn/dev.tsv
- split: test
path: data/por_Latn/test.tsv
- config_name: prs_Arab
data_files:
- split: train
path: data/prs_Arab/train.tsv
- split: validation
path: data/prs_Arab/dev.tsv
- split: test
path: data/prs_Arab/test.tsv
- config_name: quy_Latn
data_files:
- split: train
path: data/quy_Latn/train.tsv
- split: validation
path: data/quy_Latn/dev.tsv
- split: test
path: data/quy_Latn/test.tsv
- config_name: ron_Latn
data_files:
- split: train
path: data/ron_Latn/train.tsv
- split: validation
path: data/ron_Latn/dev.tsv
- split: test
path: data/ron_Latn/test.tsv
- config_name: run_Latn
data_files:
- split: train
path: data/run_Latn/train.tsv
- split: validation
path: data/run_Latn/dev.tsv
- split: test
path: data/run_Latn/test.tsv
- config_name: rus_Cyrl
data_files:
- split: train
path: data/rus_Cyrl/train.tsv
- split: validation
path: data/rus_Cyrl/dev.tsv
- split: test
path: data/rus_Cyrl/test.tsv
- config_name: sag_Latn
data_files:
- split: train
path: data/sag_Latn/train.tsv
- split: validation
path: data/sag_Latn/dev.tsv
- split: test
path: data/sag_Latn/test.tsv
- config_name: san_Deva
data_files:
- split: train
path: data/san_Deva/train.tsv
- split: validation
path: data/san_Deva/dev.tsv
- split: test
path: data/san_Deva/test.tsv
- config_name: sat_Olck
data_files:
- split: train
path: data/sat_Olck/train.tsv
- split: validation
path: data/sat_Olck/dev.tsv
- split: test
path: data/sat_Olck/test.tsv
- config_name: scn_Latn
data_files:
- split: train
path: data/scn_Latn/train.tsv
- split: validation
path: data/scn_Latn/dev.tsv
- split: test
path: data/scn_Latn/test.tsv
- config_name: shn_Mymr
data_files:
- split: train
path: data/shn_Mymr/train.tsv
- split: validation
path: data/shn_Mymr/dev.tsv
- split: test
path: data/shn_Mymr/test.tsv
- config_name: sin_Sinh
data_files:
- split: train
path: data/sin_Sinh/train.tsv
- split: validation
path: data/sin_Sinh/dev.tsv
- split: test
path: data/sin_Sinh/test.tsv
- config_name: slk_Latn
data_files:
- split: train
path: data/slk_Latn/train.tsv
- split: validation
path: data/slk_Latn/dev.tsv
- split: test
path: data/slk_Latn/test.tsv
- config_name: slv_Latn
data_files:
- split: train
path: data/slv_Latn/train.tsv
- split: validation
path: data/slv_Latn/dev.tsv
- split: test
path: data/slv_Latn/test.tsv
- config_name: smo_Latn
data_files:
- split: train
path: data/smo_Latn/train.tsv
- split: validation
path: data/smo_Latn/dev.tsv
- split: test
path: data/smo_Latn/test.tsv
- config_name: sna_Latn
data_files:
- split: train
path: data/sna_Latn/train.tsv
- split: validation
path: data/sna_Latn/dev.tsv
- split: test
path: data/sna_Latn/test.tsv
- config_name: snd_Arab
data_files:
- split: train
path: data/snd_Arab/train.tsv
- split: validation
path: data/snd_Arab/dev.tsv
- split: test
path: data/snd_Arab/test.tsv
- config_name: som_Latn
data_files:
- split: train
path: data/som_Latn/train.tsv
- split: validation
path: data/som_Latn/dev.tsv
- split: test
path: data/som_Latn/test.tsv
- config_name: sot_Latn
data_files:
- split: train
path: data/sot_Latn/train.tsv
- split: validation
path: data/sot_Latn/dev.tsv
- split: test
path: data/sot_Latn/test.tsv
- config_name: spa_Latn
data_files:
- split: train
path: data/spa_Latn/train.tsv
- split: validation
path: data/spa_Latn/dev.tsv
- split: test
path: data/spa_Latn/test.tsv
- config_name: srd_Latn
data_files:
- split: train
path: data/srd_Latn/train.tsv
- split: validation
path: data/srd_Latn/dev.tsv
- split: test
path: data/srd_Latn/test.tsv
- config_name: srp_Cyrl
data_files:
- split: train
path: data/srp_Cyrl/train.tsv
- split: validation
path: data/srp_Cyrl/dev.tsv
- split: test
path: data/srp_Cyrl/test.tsv
- config_name: ssw_Latn
data_files:
- split: train
path: data/ssw_Latn/train.tsv
- split: validation
path: data/ssw_Latn/dev.tsv
- split: test
path: data/ssw_Latn/test.tsv
- config_name: sun_Latn
data_files:
- split: train
path: data/sun_Latn/train.tsv
- split: validation
path: data/sun_Latn/dev.tsv
- split: test
path: data/sun_Latn/test.tsv
- config_name: swe_Latn
data_files:
- split: train
path: data/swe_Latn/train.tsv
- split: validation
path: data/swe_Latn/dev.tsv
- split: test
path: data/swe_Latn/test.tsv
- config_name: swh_Latn
data_files:
- split: train
path: data/swh_Latn/train.tsv
- split: validation
path: data/swh_Latn/dev.tsv
- split: test
path: data/swh_Latn/test.tsv
- config_name: szl_Latn
data_files:
- split: train
path: data/szl_Latn/train.tsv
- split: validation
path: data/szl_Latn/dev.tsv
- split: test
path: data/szl_Latn/test.tsv
- config_name: tam_Taml
data_files:
- split: train
path: data/tam_Taml/train.tsv
- split: validation
path: data/tam_Taml/dev.tsv
- split: test
path: data/tam_Taml/test.tsv
- config_name: taq_Latn
data_files:
- split: train
path: data/taq_Latn/train.tsv
- split: validation
path: data/taq_Latn/dev.tsv
- split: test
path: data/taq_Latn/test.tsv
- config_name: taq_Tfng
data_files:
- split: train
path: data/taq_Tfng/train.tsv
- split: validation
path: data/taq_Tfng/dev.tsv
- split: test
path: data/taq_Tfng/test.tsv
- config_name: tat_Cyrl
data_files:
- split: train
path: data/tat_Cyrl/train.tsv
- split: validation
path: data/tat_Cyrl/dev.tsv
- split: test
path: data/tat_Cyrl/test.tsv
- config_name: tel_Telu
data_files:
- split: train
path: data/tel_Telu/train.tsv
- split: validation
path: data/tel_Telu/dev.tsv
- split: test
path: data/tel_Telu/test.tsv
- config_name: tgk_Cyrl
data_files:
- split: train
path: data/tgk_Cyrl/train.tsv
- split: validation
path: data/tgk_Cyrl/dev.tsv
- split: test
path: data/tgk_Cyrl/test.tsv
- config_name: tgl_Latn
data_files:
- split: train
path: data/tgl_Latn/train.tsv
- split: validation
path: data/tgl_Latn/dev.tsv
- split: test
path: data/tgl_Latn/test.tsv
- config_name: tha_Thai
data_files:
- split: train
path: data/tha_Thai/train.tsv
- split: validation
path: data/tha_Thai/dev.tsv
- split: test
path: data/tha_Thai/test.tsv
- config_name: tir_Ethi
data_files:
- split: train
path: data/tir_Ethi/train.tsv
- split: validation
path: data/tir_Ethi/dev.tsv
- split: test
path: data/tir_Ethi/test.tsv
- config_name: tpi_Latn
data_files:
- split: train
path: data/tpi_Latn/train.tsv
- split: validation
path: data/tpi_Latn/dev.tsv
- split: test
path: data/tpi_Latn/test.tsv
- config_name: tsn_Latn
data_files:
- split: train
path: data/tsn_Latn/train.tsv
- split: validation
path: data/tsn_Latn/dev.tsv
- split: test
path: data/tsn_Latn/test.tsv
- config_name: tso_Latn
data_files:
- split: train
path: data/tso_Latn/train.tsv
- split: validation
path: data/tso_Latn/dev.tsv
- split: test
path: data/tso_Latn/test.tsv
- config_name: tuk_Latn
data_files:
- split: train
path: data/tuk_Latn/train.tsv
- split: validation
path: data/tuk_Latn/dev.tsv
- split: test
path: data/tuk_Latn/test.tsv
- config_name: tum_Latn
data_files:
- split: train
path: data/tum_Latn/train.tsv
- split: validation
path: data/tum_Latn/dev.tsv
- split: test
path: data/tum_Latn/test.tsv
- config_name: tur_Latn
data_files:
- split: train
path: data/tur_Latn/train.tsv
- split: validation
path: data/tur_Latn/dev.tsv
- split: test
path: data/tur_Latn/test.tsv
- config_name: twi_Latn
data_files:
- split: train
path: data/twi_Latn/train.tsv
- split: validation
path: data/twi_Latn/dev.tsv
- split: test
path: data/twi_Latn/test.tsv
- config_name: tzm_Tfng
data_files:
- split: train
path: data/tzm_Tfng/train.tsv
- split: validation
path: data/tzm_Tfng/dev.tsv
- split: test
path: data/tzm_Tfng/test.tsv
- config_name: uig_Arab
data_files:
- split: train
path: data/uig_Arab/train.tsv
- split: validation
path: data/uig_Arab/dev.tsv
- split: test
path: data/uig_Arab/test.tsv
- config_name: ukr_Cyrl
data_files:
- split: train
path: data/ukr_Cyrl/train.tsv
- split: validation
path: data/ukr_Cyrl/dev.tsv
- split: test
path: data/ukr_Cyrl/test.tsv
- config_name: umb_Latn
data_files:
- split: train
path: data/umb_Latn/train.tsv
- split: validation
path: data/umb_Latn/dev.tsv
- split: test
path: data/umb_Latn/test.tsv
- config_name: urd_Arab
data_files:
- split: train
path: data/urd_Arab/train.tsv
- split: validation
path: data/urd_Arab/dev.tsv
- split: test
path: data/urd_Arab/test.tsv
- config_name: uzn_Latn
data_files:
- split: train
path: data/uzn_Latn/train.tsv
- split: validation
path: data/uzn_Latn/dev.tsv
- split: test
path: data/uzn_Latn/test.tsv
- config_name: vec_Latn
data_files:
- split: train
path: data/vec_Latn/train.tsv
- split: validation
path: data/vec_Latn/dev.tsv
- split: test
path: data/vec_Latn/test.tsv
- config_name: vie_Latn
data_files:
- split: train
path: data/vie_Latn/train.tsv
- split: validation
path: data/vie_Latn/dev.tsv
- split: test
path: data/vie_Latn/test.tsv
- config_name: war_Latn
data_files:
- split: train
path: data/war_Latn/train.tsv
- split: validation
path: data/war_Latn/dev.tsv
- split: test
path: data/war_Latn/test.tsv
- config_name: wol_Latn
data_files:
- split: train
path: data/wol_Latn/train.tsv
- split: validation
path: data/wol_Latn/dev.tsv
- split: test
path: data/wol_Latn/test.tsv
- config_name: xho_Latn
data_files:
- split: train
path: data/xho_Latn/train.tsv
- split: validation
path: data/xho_Latn/dev.tsv
- split: test
path: data/xho_Latn/test.tsv
- config_name: ydd_Hebr
data_files:
- split: train
path: data/ydd_Hebr/train.tsv
- split: validation
path: data/ydd_Hebr/dev.tsv
- split: test
path: data/ydd_Hebr/test.tsv
- config_name: yor_Latn
data_files:
- split: train
path: data/yor_Latn/train.tsv
- split: validation
path: data/yor_Latn/dev.tsv
- split: test
path: data/yor_Latn/test.tsv
- config_name: yue_Hant
data_files:
- split: train
path: data/yue_Hant/train.tsv
- split: validation
path: data/yue_Hant/dev.tsv
- split: test
path: data/yue_Hant/test.tsv
- config_name: zho_Hans
data_files:
- split: train
path: data/zho_Hans/train.tsv
- split: validation
path: data/zho_Hans/dev.tsv
- split: test
path: data/zho_Hans/test.tsv
- config_name: zho_Hant
data_files:
- split: train
path: data/zho_Hant/train.tsv
- split: validation
path: data/zho_Hant/dev.tsv
- split: test
path: data/zho_Hant/test.tsv
- config_name: zsm_Latn
data_files:
- split: train
path: data/zsm_Latn/train.tsv
- split: validation
path: data/zsm_Latn/dev.tsv
- split: test
path: data/zsm_Latn/test.tsv
- config_name: zul_Latn
data_files:
- split: train
path: data/zul_Latn/train.tsv
- split: validation
path: data/zul_Latn/dev.tsv
- split: test
path: data/zul_Latn/test.tsv
---
# Dataset Card for SIB-200
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:** [homepage](https://github.com/dadelani/sib-200)
- **Repository:** [github](https://github.com/dadelani/sib-200)
- **Paper:** [paper](https://arxiv.org/abs/2309.07445)
- **Point of Contact:** d.adelani@ucl.ac.uk
### Dataset Summary
SIB-200 is the largest publicly available topic classification dataset based on Flores-200 covering 205 languages and dialects.
The train/validation/test sets are available for all the 205 languages.
### Supported Tasks and Leaderboards
- `topic classification`: categorize wikipedia sentences into topics e.g science/technology, sports or politics.
### Languages
There are 205 languages available :
## Dataset Structure
### Data Instances
The examples look like this for English:
```
from datasets import load_dataset
data = load_dataset('Davlan/sib200', 'eng_Latn')
# Please, specify the language code
# A data point example is below:
{
'label': 0,
'index_id': 1523,
'text': 'Mutation adds new genetic variation, and selection removes it from the pool of expressed variation.'
}
```
### Data Fields
- `label`: topic id
- `index_id`: sentence id in flores-200
- `text`: text
The topics correspond to this list:
```
"science/technology", "travel", "politics", "sports", "health", "entertainment", "geography"
```
### Data Splits
For all languages, there are three splits.
The original splits were named `train`, `dev` and `test` and they correspond to the `train`, `validation` and `test` splits.
The splits have the following sizes :
| Language | train | validation | test |
|-----------------|------:|-----------:|-----:|
| English | 701 | 99 | 204 |
## Dataset Creation
### Curation Rationale
The dataset was introduced to introduce new resources for 205 languages, many are under-served for natural language processing.
[More Information Needed]
### Source Data
The source of the data is from the news domain, details can be found here ****
#### Initial Data Collection and Normalization
The articles were word-tokenized, information on the exact pre-processing pipeline is unavailable.
#### Who are the source language producers?
The source language was produced by journalists and writers employed by the news agency and newspaper mentioned above.
### Annotations
#### Annotation process
Details can be found here **
#### Who are the annotators?
Annotators were recruited from [Masakhane](https://www.masakhane.io/)
### Personal and Sensitive Information
The data is sourced from newspaper source and only contains mentions of public figures or individuals
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
Users should keep in mind that the dataset only contains news text, which might limit the applicability of the developed systems to other domains.
## Additional Information
### Dataset Curators
### Licensing Information
The licensing status of the data is CC 4.0 Commercial
### Citation Information
Provide the [BibTex](http://www.bibtex.org/)-formatted reference for the dataset. For example:
```
@misc{adelani2023sib200,
title={SIB-200: A Simple, Inclusive, and Big Evaluation Dataset for Topic Classification in 200+ Languages and Dialects},
author={David Ifeoluwa Adelani and Hannah Liu and Xiaoyu Shen and Nikita Vassilyev and Jesujoba O. Alabi and Yanke Mao and Haonan Gao and Annie En-Shiun Lee},
year={2023},
eprint={2309.07445},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
### Contributions
Thanks to [@dadelani](https://github.com/dadelani) for adding this dataset. |
open-llm-leaderboard/details_WizardLM__WizardCoder-Python-34B-V1.0 | ---
pretty_name: Evaluation run of WizardLM/WizardCoder-Python-34B-V1.0
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [WizardLM/WizardCoder-Python-34B-V1.0](https://huggingface.co/WizardLM/WizardCoder-Python-34B-V1.0)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\nThe dataset is composed of 64 configuration, each one coresponding to one of the\
\ evaluated task.\n\nThe dataset has been created from 3 run(s). Each run can be\
\ found as a specific split in each configuration, the split being named using the\
\ timestamp of the run.The \"train\" split is always pointing to the latest results.\n\
\nAn additional configuration \"results\" store all the aggregated results of the\
\ run (and is used to compute and display the agregated metrics on the [Open LLM\
\ Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\
\nTo load the details from a run, you can for instance do the following:\n```python\n\
from datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_WizardLM__WizardCoder-Python-34B-V1.0\"\
,\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\n\
These are the [latest results from run 2023-09-30T13:26:26.501307](https://huggingface.co/datasets/open-llm-leaderboard/details_WizardLM__WizardCoder-Python-34B-V1.0/blob/main/results_2023-09-30T13-26-26.501307.json)(note\
\ that their might be results for other tasks in the repos if successive evals didn't\
\ cover the same tasks. You find each in the results and the \"latest\" split for\
\ each eval):\n\n```python\n{\n \"all\": {\n \"em\": 0.19379194630872484,\n\
\ \"em_stderr\": 0.004047912159759954,\n \"f1\": 0.2506229026845643,\n\
\ \"f1_stderr\": 0.0041031622757888245,\n \"acc\": 0.38913655258910956,\n\
\ \"acc_stderr\": 0.010569829944033455\n },\n \"harness|drop|3\": {\n\
\ \"em\": 0.19379194630872484,\n \"em_stderr\": 0.004047912159759954,\n\
\ \"f1\": 0.2506229026845643,\n \"f1_stderr\": 0.0041031622757888245\n\
\ },\n \"harness|gsm8k|5\": {\n \"acc\": 0.09476876421531463,\n \
\ \"acc_stderr\": 0.008067791560015424\n },\n \"harness|winogrande|5\"\
: {\n \"acc\": 0.6835043409629045,\n \"acc_stderr\": 0.013071868328051487\n\
\ }\n}\n```"
repo_url: https://huggingface.co/WizardLM/WizardCoder-Python-34B-V1.0
leaderboard_url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
point_of_contact: clementine@hf.co
configs:
- config_name: harness_arc_challenge_25
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|arc:challenge|25_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|arc:challenge|25_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|arc:challenge|25_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_drop_3
data_files:
- split: 2023_09_30T13_26_26.501307
path:
- '**/details_harness|drop|3_2023-09-30T13-26-26.501307.parquet'
- split: latest
path:
- '**/details_harness|drop|3_2023-09-30T13-26-26.501307.parquet'
- config_name: harness_gsm8k_5
data_files:
- split: 2023_09_30T13_26_26.501307
path:
- '**/details_harness|gsm8k|5_2023-09-30T13-26-26.501307.parquet'
- split: latest
path:
- '**/details_harness|gsm8k|5_2023-09-30T13-26-26.501307.parquet'
- config_name: harness_hellaswag_10
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hellaswag|10_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hellaswag|10_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hellaswag|10_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-28T14:24:48.520314.parquet'
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- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-28T14:24:48.520314.parquet'
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- '**/details_harness|hendrycksTest-computer_security|5_2023-08-28T14:24:48.520314.parquet'
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-28T14:24:48.520314.parquet'
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-28T14:24:48.520314.parquet'
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-28T14:24:48.520314.parquet'
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-28T14:24:48.520314.parquet'
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-28T14:24:48.520314.parquet'
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-28T14:24:48.520314.parquet'
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-28T14:24:48.520314.parquet'
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- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-28T14:24:48.520314.parquet'
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-28T14:24:48.520314.parquet'
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- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-28T14:24:48.520314.parquet'
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- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-28T14:24:48.520314.parquet'
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- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-28T14:24:48.520314.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-28T14:24:48.520314.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-28T14:24:48.520314.parquet'
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- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-28T14:24:48.520314.parquet'
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- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-28T14:24:48.520314.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-28T14:24:48.520314.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-28T14:24:48.520314.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-28T14:24:48.520314.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-08-28T14:24:48.520314.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-28T14:24:48.520314.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-08-28T14:24:48.520314.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-30T15:50:41.710615.parquet'
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- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-30T15:50:41.710615.parquet'
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- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-30T15:50:41.710615.parquet'
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- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-30T15:50:41.710615.parquet'
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- split: latest
path:
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- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-international_law|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-management|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-marketing|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-sociology|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-virology|5_2023-08-30T15:50:41.710615.parquet'
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_abstract_algebra_5
data_files:
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path:
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- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-abstract_algebra|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_anatomy_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-anatomy|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_astronomy_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-astronomy|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_business_ethics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-business_ethics|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_clinical_knowledge_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-clinical_knowledge|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_college_biology_5
data_files:
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path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_biology|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_college_chemistry_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_chemistry|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_college_computer_science_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_computer_science|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_college_mathematics_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_mathematics|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_college_medicine_5
data_files:
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path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_medicine|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_college_physics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-college_physics|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_computer_security_5
data_files:
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path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-computer_security|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_conceptual_physics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-conceptual_physics|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_econometrics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-econometrics|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_electrical_engineering_5
data_files:
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path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-electrical_engineering|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_elementary_mathematics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-elementary_mathematics|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_formal_logic_5
data_files:
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path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-formal_logic|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_global_facts_5
data_files:
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path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-28T14:24:48.520314.parquet'
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path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-global_facts|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_high_school_biology_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_biology|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_high_school_chemistry_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_chemistry|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_high_school_computer_science_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_computer_science|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_high_school_european_history_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-28T14:24:48.520314.parquet'
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path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_european_history|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_high_school_geography_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_geography|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_high_school_government_and_politics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_government_and_politics|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_high_school_macroeconomics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_macroeconomics|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_high_school_mathematics_5
data_files:
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path:
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- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_mathematics|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_high_school_microeconomics_5
data_files:
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path:
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- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_microeconomics|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_high_school_physics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-28T14:24:48.520314.parquet'
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path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_physics|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_high_school_psychology_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_psychology|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_high_school_statistics_5
data_files:
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path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_statistics|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_high_school_us_history_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_us_history|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_high_school_world_history_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-high_school_world_history|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_human_aging_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_aging|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_human_sexuality_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-human_sexuality|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_international_law_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-international_law|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_jurisprudence_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-jurisprudence|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_logical_fallacies_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-logical_fallacies|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_machine_learning_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-machine_learning|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_management_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-management|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-management|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-management|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_marketing_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-marketing|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_medical_genetics_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-medical_genetics|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_miscellaneous_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-miscellaneous|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_moral_disputes_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_disputes|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_moral_scenarios_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-moral_scenarios|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_nutrition_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-nutrition|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_philosophy_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-philosophy|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_prehistory_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-prehistory|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_professional_accounting_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_accounting|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_professional_law_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_law|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_professional_medicine_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_medicine|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_professional_psychology_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-professional_psychology|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_public_relations_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-public_relations|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_security_studies_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-security_studies|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_sociology_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-sociology|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_us_foreign_policy_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-us_foreign_policy|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_virology_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-virology|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-virology|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-virology|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_hendrycksTest_world_religions_5
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|hendrycksTest-world_religions|5_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_truthfulqa_mc_0
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- '**/details_harness|truthfulqa:mc|0_2023-08-28T14:24:48.520314.parquet'
- split: 2023_08_30T15_50_41.710615
path:
- '**/details_harness|truthfulqa:mc|0_2023-08-30T15:50:41.710615.parquet'
- split: latest
path:
- '**/details_harness|truthfulqa:mc|0_2023-08-30T15:50:41.710615.parquet'
- config_name: harness_winogrande_5
data_files:
- split: 2023_09_30T13_26_26.501307
path:
- '**/details_harness|winogrande|5_2023-09-30T13-26-26.501307.parquet'
- split: latest
path:
- '**/details_harness|winogrande|5_2023-09-30T13-26-26.501307.parquet'
- config_name: results
data_files:
- split: 2023_08_28T14_24_48.520314
path:
- results_2023-08-28T14:24:48.520314.parquet
- split: 2023_08_30T15_50_41.710615
path:
- results_2023-08-30T15:50:41.710615.parquet
- split: 2023_09_30T13_26_26.501307
path:
- results_2023-09-30T13-26-26.501307.parquet
- split: latest
path:
- results_2023-09-30T13-26-26.501307.parquet
---
# Dataset Card for Evaluation run of WizardLM/WizardCoder-Python-34B-V1.0
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/WizardLM/WizardCoder-Python-34B-V1.0
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** clementine@hf.co
### Dataset Summary
Dataset automatically created during the evaluation run of model [WizardLM/WizardCoder-Python-34B-V1.0](https://huggingface.co/WizardLM/WizardCoder-Python-34B-V1.0) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 3 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the agregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_WizardLM__WizardCoder-Python-34B-V1.0",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-09-30T13:26:26.501307](https://huggingface.co/datasets/open-llm-leaderboard/details_WizardLM__WizardCoder-Python-34B-V1.0/blob/main/results_2023-09-30T13-26-26.501307.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"em": 0.19379194630872484,
"em_stderr": 0.004047912159759954,
"f1": 0.2506229026845643,
"f1_stderr": 0.0041031622757888245,
"acc": 0.38913655258910956,
"acc_stderr": 0.010569829944033455
},
"harness|drop|3": {
"em": 0.19379194630872484,
"em_stderr": 0.004047912159759954,
"f1": 0.2506229026845643,
"f1_stderr": 0.0041031622757888245
},
"harness|gsm8k|5": {
"acc": 0.09476876421531463,
"acc_stderr": 0.008067791560015424
},
"harness|winogrande|5": {
"acc": 0.6835043409629045,
"acc_stderr": 0.013071868328051487
}
}
```
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
[More Information Needed] |
mask-distilled-one-sec-cv12/chunk_130 | ---
dataset_info:
features:
- name: logits
sequence: float32
- name: mfcc
sequence:
sequence: float64
splits:
- name: train
num_bytes: 1316821752
num_examples: 258606
download_size: 1343837371
dataset_size: 1316821752
---
# Dataset Card for "chunk_130"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
autoevaluate/autoeval-staging-eval-project-79eac003-d1e7-4d2c-ae8f-d5e71acc5a82-121117 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- glue
eval_info:
task: natural_language_inference
model: autoevaluate/natural-language-inference-not-evaluated
metrics: []
dataset_name: glue
dataset_config: mrpc
dataset_split: validation
col_mapping:
text1: sentence1
text2: sentence2
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Natural Language Inference
* Model: autoevaluate/natural-language-inference-not-evaluated
* Dataset: glue
* Config: mrpc
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. |
yimingzhang/mmlu_0 | ---
license: mit
task_categories:
- question-answering
language:
- en
pretty_name: MMLU loader with no auxiliary train set
---
This dataset contains a copy of the `cais/mmlu` HF dataset but without the `auxiliary_train` split that takes a long time to generate again each time when loading multiple subsets of the dataset.
Please visit https://huggingface.co/datasets/cais/mmlu for more information on the MMLU dataset. |
wefussell/amasum-neg-df | ---
license: mit
---
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